A Cooperative MAC Protocol for a M2M Heterogeneous Area Network

Journal of Sensor and Actuator Networks

Article A Cooperative MAC Protocol for a M2M Heterogeneous Area Network

Jamil Y. Khan *, Dong Chen and Jason Brown

School of Electrical Engineering & Computer Science, The University of Newcastle, Callaghan, NSW 2308, Australia; [email protected] (D.C.); [email protected] (J.B.) * Correspondence: [email protected]; Tel.: +61-249-216-077

Academic Editors: David Tung Chong Wong, Qian Chen, Tony T. Luo and Fan Wu Received: 18 March 2016; Accepted: 25 July 2016; Published: 28 July 2016

Abstract: With the increasing demand of Machine to Machine (M2M) communications and Internet of Things (IoT) services it is necessary to develop a new network architecture and protocols to support cost effective, distributed computing systems. Generally, M2M and IoT applications serve a large number of intelligent devices, such as sensors and actuators, which are distributed over large geographical areas. To deploy M2M communication and IoT sensor nodes in a cost-effective manner over a large geographical area, it is necessary to develop a new network architecture that is cost effective, as well as energy efficient. This paper presents an IEEE 802.11 and IEEE 802.15.4 standards-based heterogeneous network architecture to support M2M communication services over a wide geographical area. For the proposed heterogeneous network, we developed a new cooperative Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA) medium access control (MAC) protocol to transmit packets using a shared channel in the 2.4 GHz ISM band. One of the key problems of the IEEE 802.11/802.15.4 heterogeneous network in a dense networking environment is the coexistence problem in which the two protocols interfere with each other causing performance degradation. This paper introduces a cooperative MAC protocol that utilizes a new signaling technique known as the Blank Burst (BB) to avoid the coexistence problem. The proposed MAC protocol improves the network QoS of M2M area networks. The developed network architecture offers significant energy efficiency, and operational expenditure (OPEX) and capital expenditure (CAPEX) advantages over 3G/4G cellular standards-based wide area networks.

Keywords: heterogeneous network; IEEE 802.11; IEEE 802.15.4; 6LoWPAN; M2M communication; low power network

1. Introduction With the rapid expansion of Machine to Machine (M2M) communication and Internet of Things (IoT) applications in different domains, such as smart city, smart grid, healthcare, and environmental monitoring, the need for the development of low-cost, energy-efﬁcient reliable area network architectures is increasing [1]. For M2M and IoT applications, communication area networks play a very important role in moving data between various sensors, actuators, servers, and controllers. Many such applications will operate either in real-time or in delay-bounded conditions. For smart city and smart grid applications, network entities or devices, such as sensors, actuators, and controllers could be distributed over large geographical areas where devices could be located either in indoor or outdoor environments. In outdoor deployments, reliable data communication could be a challenging task due to the distributed nature of the system, heterogeneous radio propagation environments, as well as variable trafﬁc conditions [2]. At the same time, communication service requirements for the M2M/IoT applications are different compared to traditional data networks. Questions might arise, such as why should we consider the communication needs of M2M and IoT systems together?

J. Sens. Actuator Netw. 2016, 5, 12; doi:10.3390/jsan5030012 www.mdpi.com/journal/jsan J. Sens. Actuator Netw. 2016, 5, 12 2 of 21

Traditionally M2M solutions typically use point-to-point links using wired or wireless connectivity. On the other hand, IoT solutions rely on Internet Protocol (IP) networks to interface data to a cloud or middleware platform. M2M communication is more concerned with the lower-level networking functionalities [3]. The IoT represents connectivity beyond transmission from one machine to another. Obviously there is a certain overlap between these two systems; that is, the need to use lower-level network protocols and architecture. Hence, we explore the communication needs for both systems. Key requirements of IoT applications are listed below:

‚ Need to serve medium to high network device density (devices/sq.km), generating small bursts of data with variable duty cycle. ‚ Low energy availability for computing and communication needs. ‚ Very high reliability with variable Quality of Service (QoS) requirements. ‚ Low, or no, terminal mobility. ‚ Asymmetric trafﬁc ﬂow with higher capacity requirements on the uplink (i.e., from an end device to a network-based data sink).

To serve distributed IoT applications with the above requirements, different wireless network architectures can be used. Traditional cellular wide area networks could be used to support such applications which generally have higher capital expenditure (CAPEX) and operational expenditure (OPEX) costs. Another approach could be to use unlicensed band short range wireless networks where multi-hop or mesh wireless network architecture can be used to cover large geographical areas. Traditional cellular networks, such as 3G/4G-based standards may not efﬁciently support all of the needs of IoT applications due to high signaling requirements, infrastructure, and energy costs [4]. Additionally, cellular networks may not provide seamless connectivity to all devices due to spatial and temporal fading effects. The M2M communications functional model proposed by the European Telecommunications Standards Institute (ETSI) standard suggests that cellular networks could provide core network support and aggregated data from gateways could be transmitted over cellular networks [5]. Hence, to support the device level communication, it is necessary to develop a new wireless sensor network architecture that can deliver QoS requirements for different applications. The two main drawbacks of traditional wireless sensor networks are lack of deterministic QoS support and the scalability problem [6]. The main contribution of this paper is a new low-cost heterogeneous network architecture that can support IoT data transmission needs in a wide area with the necessary QoS requirements. The heterogeneous wireless network architecture has been developed to operate in the unlicensed band where inter and intra-network interferences could be a critical problem. This proposed architecture introduces a new inter network cooperative medium access control (MAC) layer-based signaling protocol to mitigate the above interference problem and to improve the throughput of an M2M area network based on short range wireless networking standards. The objective of the paper is to present new directions on the low-cost wide area network design for M2M and IoT applications using unlicensed band standards. The paper structure is as follows: Section2 brieﬂy reviews typical smart city IoT and M2M communication requirements. Section3 reviews M2M communication network architectures and requirements; Section4 discusses M2M area network design issues and reviews the IEEE 802.15.4 and IEEE 802.11 networking standards for the area network design; Section5 presents a new IPv6 Low power Wireless Personal Area Network 6LoWPAN) and IEEE 802.11 standards-based heterogeneous M2M area network architecture where the coexistence problem is mitigated by using a cooperative MAC protocol; Section6 presents extensive simulation results and performance analysis obtained from a custom OPNET (Optimized Network Engineering Tool)-based simulation model; and conclusions are drawn in Section7. J. Sens. Actuator Netw. 2016, 5, 12 3 of 21

2. IoT Communication Requirements for Smart City Applications IoT is one of the distributed computing areas where a large number of applications are appearing in different domains, such as smart city, smart grid, e-health, vehicular communications, etc. [7,8]. One of the key requirements of IoT applications is to move data between different entities in an autonomous manner by using the lower-level M2M communication architecture. The QoS requirements of IoT applications could be significantly different from conventional data communications used in human-to-human (H2H) and human-to-machine (H2M) communications [9]. Application QoS requirements are generally met by the underlying networks, hence, the network design process must address all of the application requirements. IoT applications are gradually evolving and their QoS requirements depend on the application domain. In this section we restrict our discussions to smart city and smart grid based applications. According to Gartner Inc., smart cities will support 6.5 billion connected devices by 2016 to provide a range of services [10]. Key services within smart cities will be healthcare, public services, smart buildings, smart homes, transport, and utility sectors. Applications in smart city and smart grid domains can be classified into three different categories; monitoring, device/actuator control, and demand management. Traffic generated by these applications can be characterized by its basic properties, such as the data burst/packet arrival rate, arrival pattern, and the packet/data burst length. The pattern of packet arrivals depends upon the type of application and whether periodic, aperiodic, random and/or events could be triggered. In the case of an event-triggered system, the data arrival process will be influenced by monitoring events or associated activities within a monitoring network. For example, in sensor actuator network applications, data can be triggered by other monitoring events and, hence, the data generation probability will depend on the event characteristics which can be stochastic in nature. In event triggered systems, data generation characteristics could be significantly different from H2M and H2H applications. Some of the general requirements of M2M applications and traffic are listed below.

‚ Large number of data devices distributed over a wide area where node density in terms of nodes/sq. km could be high, representing a dense operating environment. ‚ Delay-sensitive or time-controlled; a packet needs to be delivered within a fixed time period. ‚ Delay-tolerant; generally seen as elastic traffic that can support variable and longer delays. ‚ Low packet loss tolerance; many applications may not support any or very little packet losses. ‚ Small data burst transmissions; applications generate small data bursts, which need to be transmitted independently. ‚ Data asymmetry with higher data volume on uplinks; mostly for monitoring and control applications. ‚ Event-based traffic generation, traffic characteristics, and intensity could depend on physical events in a network. ‚ Priority alarm and/or traffic; high priority traffic that may coexist with other class of traffic. ‚ Point-to-point and point-to-multipoint packet transmissions supporting multicast services.

Servicing a single traffic class either with fixed or variable interarrival time is relatively easier. Many of the M2M/IoT applications will generate a single packet per data burst. However, the event triggered or surveillance applications could generate data bursts where multiple packets could be generated in successions within a data burst. In such applications the packet inter-arrival time could vary depending on the event [9]. Quite often event-triggered data is difficult to handle through conventional data networks because such traffic demands higher priorities where network resources need prior allocation. Such applications could be seen in a smart grid environment supporting fault detection and management applications. Similarly, traffic monitoring applications in intelligent transportation systems could generate such event-based traffic. Traffic arrival processes and data characteristics could significantly influence network design for M2M/IoT applications. Table1 lists J. Sens. Actuator Netw. 2016, 5, 12 4 of 21 some of the communication requirements of smart grid and smart city applications [11–13]. The table shows traffic QoS requirements, data transmission link requirements, and traffic generation processes. Table1 demonstrates that delay requirements could vary significantly from a few milliseconds to many seconds. Some applications might tolerate packet losses, whereas several classes of applications can compensate for packet losses using either the data link layer and/or transport layer retransmission procedures. These layers can use an Automatic Repeat reQuest (ARQ) procedure. Table1 shows that most of the smart city and smart grid applications are heavily uplink-biased (device to a network-based data sink link) traffic. Even in the case of demand response systems, traffic may not be fully symmetrical. In this paper, the link that is carrying data from end devices to a network-based data sink is referred as the uplink (UL). Similarly, the link carrying data from the data sink to end devices is referred as the downlink (DL).

3. M2M Network Architecture and Requirements Network design requirements for M2M and IoT applications are significantly different from H2H and M2H communications due to the nature of the services. Data and communication requirements of H2H and H2M systems are mainly dominated by higher data rate and low latency. These networks also need to support data rate asymmetry with higher data volume on the downlink for applications, such as file download and video streaming. Requirements of M2M applications are discussed in Section2. Figure1 shows a functional M2M communication network architecture based on the ETSI standard [5,14]. The architecture is divided into two domains; the device and gateway, and the network. The device and gateway domain is composed of M2M devices, area networks, applications, and the M2M gateway. The network domain mainly consists of access and core networks, M2M management functions, and various M2M applications. The device and gateway domain can support two types of M2M devices where enhanced devices can have direct connectivity to application servers via the access network, whereas other devices with lower capabilities can only connect to the network domain via an M2M gateway through the area network as shown in the figure. M2M devices can also be connected to the network domain via multiple M2M gateways through different access networks. Network elements in the device and gateway domain should serve the M2M traffic directly from source nodes which are distributed over a wide area. These devices will generate short data bursts and have low energy consumption requirements. On the other hand, in the network domain, the data connections are mostly served by the gateways and enhanced M2M devices where data bursts are generally larger, with less restrictions on energy consumption. Connectivity in this domain can be supported by conventional cellular networking standards, as well as high data rate short range wireless networking standards. To support M2M communication requirements over a cellular network, new radio resource allocation techniques need to be developed so that short and infrequent data bursts can be efficiently served [15,16]. J. Sens. Actuator Netw. 2016, 5, 12 5 of 21

Table 1. Smart grid and smart city application communication requirements.

Application Delay Requirements (maximum) Packet Loss (%) Traffic Flow Direction Traffic Type Smart Grid: Grid protection information 1–10 ms 0 UL, DL Event triggered, timed Breaker closure 16 ms 0 UL, DL Event triggered, timed Transformer protection/control 16 ms 0 UL, DL Event triggered, timed PMU (Phase Measurement Unit)—synchrophasor 20 ms <1 UL Periodic SCADA periodic measurements 100 ms <2 UL, DL Periodic, on demand DSM (Demand Side Management) services 200–500 ms 0 UL, DL Periodic, aperiodic, event based Automatic meter reading—demand 250 ms 0 UL, DL On demand Fault isolation & service restoration 100–1000 ms 0 UL, DL Event based, planned Automatic meter reading—regular reads >15 s <5 UL Periodic Smart City: Building structure monitor Data: 30 min; Alarm: 10 s Variable UL, DL Periodic, event based Waste management Data: 30 min Variable UL Periodic, on demand Traffic congestion Data: 5 min Variable UL, DL Periodic, event based, on demand Smart parking Data: <1 min 0 UL, DL On demand Smart lighting control Data: <1 mins 0 UL, DL On demand Health monitoring Data: 1–5 min; Alarm: <1 min 0 UL, DL Periodic, on demand J. Sens. Actuator Netw. 2016, 5, 12 4 of 20 sink is referred as the uplink (UL). Similarly, the link carrying data from the data sink to end devices is referred as the downlink (DL).

3. M2M Network Architecture and Requirements Network design requirements for M2M and IoT applications are significantly different from H2H and M2H communications due to the nature of the services. Data and communication requirements of H2H and H2M systems are mainly dominated by higher data rate and low latency. These networks also need to support data rate asymmetry with higher data volume on the downlink for applications, such as file download and video streaming. Requirements of M2M applications are discussed in Section 2. Figure 1 shows a functional M2M communication network architecture based on the ETSI standard [5, 14]. The architecture is divided into two domains; the device and gateway, and the network. The device and gateway domain is composed of M2M devices, area networks, applications, and the M2M gateway. The network domain mainly consists of access and core networks, M2M management functions, and various M2M applications. The device and gateway domain can support two types of M2M devices where enhanced devices can have direct connectivity to application servers via the access network, whereas other devices with lower capabilities can only connect to the network domain via an M2M gateway through the area network as shown in the figure. M2M devices can also be connected to the network domain via multiple M2M gateways through different access networks. Network elements in the device and gateway domain should serve the M2M traffic directly from source nodes which are distributed over a wide area. These devices will generate short data bursts and have low energy consumption requirements. On the other hand, in the network domain, the data connections are mostly served by the gateways and enhanced M2M devices where data bursts are generally larger, with less restrictions on energy consumption. Connectivity in this domain can be supported by conventional cellular networking standards, as well as high data rate short range wireless networking standards. J.To Sens. support Actuator M2M Netw. 2016communication, 5, 12 requirements over a cellular network, new radio resource allocation6 of 21 techniques need to be developed so that short and infrequent data bursts can be efficiently served [15,16].

FigureFigure 1.1. FunctionalFunctional architecturearchitecture ofof aa M2MM2M networknetwork basedbased onon thetheETSI ETSI speciﬁcation.specification.

4. M2M Area Network Design This section reviews the design requirements of M2M area networks using short-range wireless networking standards. M2M area networks will directly serve end devices which are spread over a geographical area. In order to collect data from distributed devices, it is necessary to provide seamless connectivity from devices to data servers. Direct connectivity from data devices to data servers will not be feasible due to the high density of nodes and transmission power requirements. It will be useful to relay data from devices via local gateways to the server using multi-hop links. Since end devices will generate infrequent data bursts, appropriate network topologies and MAC protocols need to be selected to offer seamless connectivity with maximum transmission efﬁciency at a minimum cost. A low power wireless sensor network architecture is considered to be the most suitable for M2M area networks due to its lower cost and energy requirements. Wireless sensor networks generally use one of several network topologies for data transmission. The main network topologies used are: star, peer-to-peer, tree, and mesh [17]. The star topology is the most commonly used topology for small-size sensor networks, whereas the tree and mesh network architectures extend the communication range. The star topology uses a coordinator to exchange data among connected nodes; in wireless sensor networks the star topology is also referred to as the cluster topology where the coordinator becomes the cluster head. The transmission range of the cluster topology can be extended by using the cluster tree topology. In the cluster tree topology, multiple clusters communicate with each other either via cluster heads or routers as shown in Figure2. The cluster tree topology could be a suitable architecture for M2M area networks as the routers or gateways could be placed close to end devices reducing transmission power consumption and avoiding radio channel impairments. J. Sens. Actuator Netw. 2016, 5, 12 5 of 20

4. M2M Area Network Design This section reviews the design requirements of M2M area networks using short-range wireless networking standards. M2M area networks will directly serve end devices which are spread over a geographical area. In order to collect data from distributed devices, it is necessary to provide seamless connectivity from devices to data servers. Direct connectivity from data devices to data servers will not be feasible due to the high density of nodes and transmission power requirements. It will be useful to relay data from devices via local gateways to the server using multi-hop links. Since end devices will generate infrequent data bursts, appropriate network topologies and MAC protocols need to be selected to offer seamless connectivity with maximum transmission efficiency at a minimum cost. A low power wireless sensor network architecture is considered to be the most suitable for M2M area networks due to its lower cost and energy requirements. Wireless sensor networks generally use one of several network topologies for data transmission. The main network topologies used are: star, peer-to-peer, tree, and mesh [17]. The star topology is the most commonly used topology for small-size sensor networks, whereas the tree and mesh network architectures extend the communication range. The star topology uses a coordinator to exchange data among connected nodes; in wireless sensor networks the star topology is also referred to as the cluster topology where the coordinator becomes the cluster head. The transmission range of the cluster topology can be extended by using the cluster tree topology. In the cluster tree topology, multiple clusters communicate with each other either via cluster heads or routers as shown in Figure 2. The cluster tree topology could be a suitable architecture foJ. Sens.r M2M Actuator area Netw. networks2016, 5, 12as the routers or gateways could be placed close to end devices reducing7 of 21 transmission power consumption and avoiding radio channel impairments.

Figure 2. Cluster tree network architecture. Network operation showing data exchange between a Figure 2. Cluster tree network architecture. Network operation showing data exchange between a server and end devices. server and end devices. The medium access control protocol is another critical design issue for M2M area networks [18]. An M2MThe mediumarea network access could control be considered protocol is as another a local criticaland/or designpersonal issue area for network M2M areawhere networks one of three [18]. Andifferent M2M classes area network of MAC could protocols be considered is used. These as a protocols local and/or are: scheduled personal areaaccess, network random where access one, an ofd pollingthree different [17]. Scheduled classes of access MAC and protocols polling is used.protocols These generally protocols require are: scheduled more control access, signaling random support access, comparedand polling to [17random]. Scheduled access protocols access and and polling are generally protocols not generally suitable requirefor low more-power control area networks. signaling Highsupport levels compared of signaling to random increases access power protocols consumption and are and generally computational not suitable complexities. for low-power On the other area hand,networks. random High access levels protocols of signaling generally increases have power lower consumptionsignaling requirements and computational at the expense complexities. of QoS degradation,On the other particularly hand, random at high access traffic protocols load. Random generally access have networks lower signaling can maintain requirements reasonable at QoS the expense of QoS degradation, particularly at high trafﬁc load. Random access networks can maintain reasonable QoS as long as trafﬁc load is low to moderate. Hence, it is necessary to develop advanced resource allocation techniques to maintain QoS in M2M networks. In the last two decades, a number of short range wireless networking standards have emerged to support communications in local and personal area networking environments. Out of the many standards, several wireless networking standards have further progressed and become the potential candidates for M2M communication networks. In this section, we review the IEEE 802.15.4/6LoWPAN and IEEE 802.11 standards for M2M network infrastructure design in the device and gateway domain. There are other short range wireless standards, such as Bluetooth/IEEE 802.15.1, Wireless HART, LoRa, ECMA 368, and ISA 100.11a which could have roles in M2M network design, but considering the paper size we will limit our discussions to two main IEEE short-range wireless standards.

4.1. IEEE 802.11 MAC Standard The IEEE 802.11 wireless local area network (WLAN) standard has been evolving over the last two decades. The 802.11 standard has been developed mainly to act as an access network using unlicensed spectrum in the 2.4 GHz and 5 GHz bands. The standard has evolved from a low data rate network to a gigabit network, supporting broadband connectivity. Table2 lists some of the key 802.11 standards with selected features. The table shows that revised versions of the standard have resulted in increased data rates over time. Very recently, the 802.11ah standard has been developed to support M2M and IoT communications using narrow band channels in a spectrum band below 1 GHz [19]. This standard can support a large number of devices in outdoor environments, J. Sens. Actuator Netw. 2016, 5, 12 8 of 21 supporting sensor networking requirements. The IEEE 802.11p is another variant of the standard that has been developed for vehicular networks to support vehicular M2M communication systems.

Table 2. IEEE 802.11 standards development history.

Network Frequency Band Transmission Data Transmission Release Date Bandwidth (MHz) Standard: IEEE (GHz) Rates Mbits/s Techniques 802.11 June 1997 2.4 22 1,2 DSSS 1, FHSS 2 802.11a September 1999 5 20 6,9,12,18,24,36,48, 54 OFDM 3 802.11g June 2003 2.4 20 6,9,12,18,24,36,48, 54 OFDM 20: 7.2 to 72.2 4 802.11n October 2009 2.4, 5 MIMO -OFDM 40: 15 to 150 4 streams 20: 7.2 to 96.3 40: 15 to 200 802.11ac December 2013 5 MIMO-OFDM 80: 32.5 to 433 8 streams 160: 65 to 866 OFDM, Single 802.11ad December 2012 60 2160 Up to 7000 carrier 1: 0.3 to 4.0, 0.15 (MCS10) 2: 0.65 to 7.8 802.11ah October 2013 0.9 4: 1.35 to 18 MIMO-OFDM 8: 2.925 to 39 16: 5.85 to 78 802.11p July 2010 5.9 10: 3 to 27 OFDM 1: DSSS: direct sequence spread spectrum. 2: FHSS: frequency hopping spread spectrum. 3: OFDM: orthogonal frequency division multiplexing. 4: MIMO: multiple input multiple output.

For M2M communications, the 802.11 standard and in particular the 802.11ah variant, could play a key role, offering flexibility in designing and implementing M2M area networks. The standard operates based on the carrier sense multiple access with collision avoidance (CSMA/CA) protocol. The standard does not limit the number of stations that can associate in a network and, hence, is suitable for M2M communications. However, the actual number of stations in a network will be limited by the QoS requirements, since it is a contention/random access-based network. For M2M applications, it is necessary to use appropriate techniques to minimize the effect of contention in dense networking environments. Most of the 802.11 devices use physical carrier sensing techniques; however, virtual carrier sensing techniques could be more energy efficient. The IEEE 802.11 standard specifies two different virtual carrier sensing mechanisms. The original virtual carrier sensing technique uses a network allocation vector (NAV) whereby network devices can overhear current transmissions to schedule their next channel sensing time to avoid collisions. A new virtual carrier sensing technique known as response indication deferral (RID) has been proposed for the IEEE 802.11ah standard. The difference between NAV and RID is that, in the case of RID, a collision-sensing flag is set immediately after the PHY layer header reception instead of after a full packet reception. In the case of RID, devices can resolve the collision status quickly to schedule transmission and sleeping periods in an efficient manner to reduce energy consumption, as well as to minimize contention levels in a network. It is worthwhile to mention that virtual carrier sensing is more energy efficient than physical carrier sensing techniques because, in the case of the former, a device does not need to sense the channel multiple times. As mentioned earlier, one of the key concerns of the CSMA/CA protocol is the lack of QoS support. The IEEE 802.11e standard introduced the enhanced distributed channel access (EDCA) technique to offer priorities to traffic classes as well as to offer QoS guarantees. However, the EDCA technique is not suitable for transmitting infrequent short bursts of traffic as seen in M2M and IoT applications. The emerging 802.11ah standard tries to address the contention problem in a dense networking environment by introducing a new technique known as restricted access window (RAW) that attempts to restrict contention levels by reducing channel access attempts over a longer period. The RAW technique divides network devices into groups and splits the transmission frame into slots. Contention levels within each time slot can be contained by restricting the number of terminals. The RAW technique can be seen as a combined TDM (Time Division Multiplex)/CSMA/CA channel structure. The technique needs to be further J. Sens. Actuator Netw. 2016, 5, 12 9 of 21 developed in order to optimize the RAW architecture so that the QoS of different applications can be supported. Other benefits of the emerging 802.11ah standard are: (i) short maximum header size of 28 bytes instead of 40 bytes, the MAC layer also supports a short six-byte header; (ii) supports a transmission range up to 1 km for a single hop link; and (iii) the suggested transmission power level is between less than 10 mW and 1 W depending on country regulations. The emerging standard has been designed targeting M2M networks; however, further research work needs to be carried out to optimize algorithms and network architecture.

4.2. IEEE 802.15.4 Standard In recent times, the IEEE 802.15.4 network standard has received signiﬁcant attention as a low power wireless sensor network and is the basis of Zigbee [20]. The standard deﬁnes the physical and medium access control (MAC) layers for low-rate wireless personal area networks (LR-WPAN).

TheJ. Sens. main Actuator advantages Netw. 2016, 5 of, 12 the standard are reliable data transfer over short transmission distance,8 of 20 low energy requirements, as well as lower hardware and installation costs. The physical layer supports threeperiod different (CAP) and frequency the contention bands: free 2.45 period GHz with (CFP). 16 In channels, the CAP 915 period, MHz end with devices 10 channels, can transmit and 868 packets MHz withusing one the channel.CSMA/CA The mechanism. data rate supported In the CFP by part the standardof the frame varies, fixed between time 20slots kbits/s are used to 250 which kbits/s. are Areferred new extension as guaranteed of the timestandard slots known(GTSs). as The 802.15.4g GTSs are supports allocated a data in advance rate of 1 where Mbits/s. devicesThe new can physicaltransmit their layer packets also supports in a contention advanced free functions mode. The such CAP as and channel CFP durations selection, are link adjustable quality estimation,depending channelon the application energy detection needs. The and active clear period channel is followed assessment by an (CCA). inactive In period the following when all end paragraphs, devices thecan 802.15.4remain in MAC the sleep layer mode design to will conserv be discussed.e energy.

Figure 3.3. IEEE 802.15.4 superframe structure.

The super frame structure is controlled by two main parameters. Beacon Order (BO) controls the The MAC layer of the standard deﬁnes two types of node; reduced functionality device (RFD) duration between two beacon frames known as the Beacon Interval (BI). Another parameter known and Full Functional Device (FFD). An FFD is enabled with a full set of MAC layer functionalities as the Superframe Order (SO) regulates the length of the CAP period. The beacon interval (BI), which allow this type of device to act as a network coordinator whereas an RFD device can only act superframe duration (SD) and duty cycle (DC) are represented by Equations (1)–(3). as an end device, such as a sensor/actuator node. The standard can support both star/cluster and peer-to-peer topologies.퐵퐼 The= standard푎퐵푎푠푒푆푢푝푒푟푓푟푎푚푒퐷푢푟푎푡푖표푛 supports both beacon-based× 2퐵푂 (푠푦푚푏표푙푠 and non-beacon-based) packet(1) transmission techniques. This work only concentrates on the beacon-based packet transmission 푆퐷 = 푎퐵푎푠푒푆푢푝푒푟푓푟푎푚푒퐷푢푟푎푡푖표푛 × 2푆푂(푠푦푚푏표푙푠) (2) techniques. Figure3 shows the superframe structure of the IEEE 802.15.4 standard. The frame starts 푆퐷 with a beacon indicating the start of a transmission퐷퐶 = cycle.⁄퐵퐼 The beacons are separated by the beacon(3) interval duration. The transmission interval is divided into two portions represented by active and For the above equations, the following relation must hold 0 ≤ SO ≤ BO ≤ 14. inactive periods. The active period can be further divided into 16 time slots, which can be used by The IEEE 802.15.4 standard regulates the minimum superframe duration, which is equal to 960 end devices to access the channel to transmit packets. The active period can be further categorized symbols (15.36 ms). One time slot occupies 960/16 = 60 symbols (0.96 ms). Beacons contain control management information, such as the start and end of a superframe, address information, and the number of time slots allocated to the GTS service. If the CFP is disabled, then the entire active part of a super frame becomes the CAP duration. The CFP, in contrast, can allocate up to seven GTS slots that result in the minimum CAP length of 440 symbols, which is equal to eight time slots. This ensures sufficient time in which packets can be transmitted. Moreover, after a transmission, an acknowledgement for the received packet is sent back immediately to provide a reliable communication service by the MAC layer. A packet transmission has to be finished within one interframe spacing (IFS), otherwise the transmission will be deferred to the next superframe. The 6LoWPAN standard has been developed by the Internet Engineering Task Force (IETF) group by incorporating the IP (Internet Protocol) and associated layers on top of the IEEE 802.15.4 protocol stack [21]. The 6LoWPAN standard is capable of supporting both M2M and IoT applications. Figure 4 shows the 6LoWPAN protocol stack. The adaptation layer is mainly used to compress 40 bytes IP header in to a two-byte field to be accommodated within a small size 128-byte 802.15.4 packet.

J. Sens. Actuator Netw. 2016, 5, 12 10 of 21 into the contention access period (CAP) and the contention free period (CFP). In the CAP period, end devices can transmit packets using the CSMA/CA mechanism. In the CFP part of the frame, ﬁxed time slots are used which are referred as guaranteed time slots (GTSs). The GTSs are allocated in advance where devices can transmit their packets in a contention free mode. The CAP and CFP durations are adjustable depending on the application needs. The active period is followed by an inactive period when all end devices can remain in the sleep mode to conserve energy. The super frame structure is controlled by two main parameters. Beacon Order (BO) controls the duration between two beacon frames known as the Beacon Interval (BI). Another parameter known as the Superframe Order (SO) regulates the length of the CAP period. The beacon interval (BI), superframe duration (SD) and duty cycle (DC) are represented by Equations (1)–(3).

BI “ aBaseSuperframeDuration ˆ 2BO psymbolsq (1)

SD “ aBaseSuperframeDuration ˆ 2SO psymbolsq (2)

DC “ SD{BI (3)

For the above equations, the following relation must hold 0 ď SO ď BO ď 14. The IEEE 802.15.4 standard regulates the minimum superframe duration, which is equal to 960 symbols (15.36 ms). One time slot occupies 960/16 = 60 symbols (0.96 ms). Beacons contain control management information, such as the start and end of a superframe, address information, and the number of time slots allocated to the GTS service. If the CFP is disabled, then the entire active part of a super frame becomes the CAP duration. The CFP, in contrast, can allocate up to seven GTS slots that result in the minimum CAP length of 440 symbols, which is equal to eight time slots. This ensures sufficient time in which packets can be transmitted. Moreover, after a transmission, an acknowledgement for the received packet is sent back immediately to provide a reliable communication service by the MAC layer. A packet transmission has to be finished within one inter-frame spacing (IFS), otherwise the transmission will be deferred to the next superframe. The 6LoWPAN standard has been developed by the Internet Engineering Task Force (IETF) group by incorporating the IP (Internet Protocol) and associated layers on top of the IEEE 802.15.4 protocol stack [21]. The 6LoWPAN standard is capable of supporting both M2M and IoT applications. Figure4 shows the 6LoWPAN protocol stack. The adaptation layer is mainly used to compress 40 bytes IP headerJ. Sens. Actuator in to aNetw. two-byte 2016, 5, field 12 to be accommodated within a small size 128-byte 802.15.4 packet. 9 of 20

Figure 4.4. 6LoWPAN protocolprotocol stack.stack.

For an M2M area network, it is possible to use the 802.11/802.15.4 standards in a standalone For an M2M area network, it is possible to use the 802.11/802.15.4 standards in a standalone mode. However, these standards have their own comparative limitations. The 802.11 standard’s main mode. However, these standards have their own comparative limitations. The 802.11 standard’s drawback is higher energy consumption compared to the IEEE 802.15.4 standard. The main advantages of the 802.11 standard are the increased data rate and a longer transmission range. The main relative advantage of the IEEE 802.15.4 is low power consumption. The main disadvantages of the 802.15.4 standard are low transmission data rate and a shorter transmission range. In this work, we propose a heterogeneous network architecture using both IEEE 802.11 and IEEE 802.15.4 standards to develop a high capacity, low-power, and long-range M2M area network exploiting the advantages of both standards.

5. M2M Heterogeneous Area Network In this section, we present a heterogeneous M2M access network architecture based on IEEE 802.11 and IEEE 802.15.4 standards. The proposed heterogeneous network can support a large geographical area with deterministic QoS for M2M applications. One of the main problems of such a heterogeneous architecture is the overlap of the transmission spectrum in the 2.4 GHz band; particularly when operating in a dense networking environment. Spectrum overlap is referred to as the coexistence problem. The coexistence problem can generally arise when two or more co-located dissimilar networks share the same transmission spectrum with bands which are either partially or fully overlapped [22]. To mitigate the coexistence problem, advanced channel management algorithms need to be developed. The IEEE 802.15.4 standard currently supports a number of operating spectrum bands; the main spectrum bands are the 2.4 GHz ISM (Industrial, Scientific, and Medical) band and the sub-GHz band between 700–900 MHz. The IEEE 802.11x currently uses the 2.4 GHz and 5 GHz bands for all current versions of the standard. The emerging IEEE 802.11ah standard will operate in the 900 MHz band. Hence, these network devices could generate inter-domain collisions (between 802.15.4/802.11 devices) since both standards are using the CSMA/CA protocol for packet transmissions. This work proposes a heterogeneous network architecture using 802.11 b/g and 802.15.4 standards to operate in the 2.4 GHz band that avoids the coexistence problem using a cooperative MAC protocol. For the smart grid and IoT applications, a lower transmission frequency will be more useful due to lower path loss which, in turn, could reduce transmission power and prolong the battery life. Figure 5 shows the operating spectra of the IEEE 802.15.4 and the IEEE 802.11b/g standards in the 2.4 GHz band. It can be seen from the figure that three IEEE 802.11b/g channels can generate interference for 12 out of 16 channels of the IEEE 802.15.4 standard. Additionally, the IEEE 802.11x channels are wider compared to the IEEE 802.15.4 channels. This overlap of transmission channels introduces a serious coexistence problem [23,24]. The IEEE 802.15.4 standard has the option of using a frequency hopping technique to avoid interference among network devices. Transceivers can select one of the sixteen transmission channels to avoid interference from co-located transmitters. However, such a solution may not be effective for a dense heterogeneous network environment where the number of co-located transceivers will be high, particularly considering the larger transmission range of 802.11 devices.

J. Sens. Actuator Netw. 2016, 5, 12 11 of 21 main drawback is higher energy consumption compared to the IEEE 802.15.4 standard. The main advantages of the 802.11 standard are the increased data rate and a longer transmission range. The main relative advantage of the IEEE 802.15.4 is low power consumption. The main disadvantages of the 802.15.4 standard are low transmission data rate and a shorter transmission range. In this work, we propose a heterogeneous network architecture using both IEEE 802.11 and IEEE 802.15.4 standards to develop a high capacity, low-power, and long-range M2M area network exploiting the advantages of both standards.

5. M2M Heterogeneous Area Network In this section, we present a heterogeneous M2M access network architecture based on IEEE 802.11 and IEEE 802.15.4 standards. The proposed heterogeneous network can support a large geographical area with deterministic QoS for M2M applications. One of the main problems of such a heterogeneous architecture is the overlap of the transmission spectrum in the 2.4 GHz band; particularly when operating in a dense networking environment. Spectrum overlap is referred to as the coexistence problem. The coexistence problem can generally arise when two or more co-located dissimilar networks share the same transmission spectrum with bands which are either partially or fully overlapped [22]. To mitigate the coexistence problem, advanced channel management algorithms need to be developed. The IEEE 802.15.4 standard currently supports a number of operating spectrum bands; the main spectrum bands are the 2.4 GHz ISM (Industrial, Scientiﬁc, and Medical) band and the sub-GHz band between 700–900 MHz. The IEEE 802.11x currently uses the 2.4 GHz and 5 GHz bands for all current versions of the standard. The emerging IEEE 802.11ah standard will operate in the 900 MHz band. Hence, these network devices could generate inter-domain collisions (between 802.15.4/802.11 devices) since both standards are using the CSMA/CA protocol for packet transmissions. This work proposes a heterogeneous network architecture using 802.11 b/g and 802.15.4 standards to operate in the 2.4 GHz band that avoids the coexistence problem using a cooperative MAC protocol. For the smart grid and IoT applications, a lower transmission frequency will be more useful due to lower path loss which, in turn, could reduce transmission power and prolong the battery life. Figure5 shows the operating spectra of the IEEE 802.15.4 and the IEEE 802.11b/g standards in the 2.4 GHz band. It can be seen from the ﬁgure that three IEEE 802.11b/g channels can generate interference for 12 out of 16 channels of the IEEE 802.15.4 standard. Additionally, the IEEE 802.11x channels are wider compared to the IEEE 802.15.4 channels. This overlap of transmission channels introduces a serious coexistence problem [23,24]. The IEEE 802.15.4 standard has the option of using a frequency hopping technique to avoid interference among network devices. Transceivers can select one of the sixteen transmission channels to avoid interference from co-located transmitters. However, such a solution may not be effective for a dense heterogeneous network environment where the number of co-located transceivers willJ. Sens. be Actuator high, particularlyNetw. 2016, 5, 12 considering the larger transmission range of 802.11 devices. 10 of 20

Figure 5 5.. Spectrum allocation of IEEE 802.15.4 and IEEE 802.11b networking standards.

The proposed heterogeneous network architecture is shown in Figure 6. The network is made up of M sensor nodes divided into N clusters where P (P = M/N) is the number of nodes supported by each of the 6LoWPAN routers acting as the head of each cluster. The 6LoWPAN routers interface to a multi- frequency dual-radio router (MFDRR) gateway using 6LoWPAN interfaces. The MFDRR accepts data from the 6LoWPAN routers, aggregates data blocks, and transmits them to a data sink using an 802.11 link. This unique MFDRR architecture has been developed to avoid the coexistence problem. As the name suggests, the MFDRR can support multiple channels to accept data from different 802.15.4 clusters. In this network, different channels are used by neighboring clusters to avoid mutual cluster interferences. Hence, to accommodate dense networking environments, multiple 6LoWPAN radio interfaces are used at the MFDRR tuned to different carrier frequencies. In Figure 6, red clusters use one carrier frequency while the green clusters use a non-overlapping different carrier frequency. As shown in the figure, the neighboring clusters will avoid interference due to use of alternating carrier frequencies. Additionally, the transmission power of end devices is limited such that packets can only be received by the local cluster heads. Hence, by using alternating carrier frequencies and limiting transmission power, inter-cluster interference can be avoided. The red and green dotted circles show the transmission distances of 802.15.4 end devices and the black dotted circles show the transmission distance of the 802.11 transmitter in the MFDRR. It can be easily seen that the 802.11 transmitter in the MFDRR will interfere with all 802.15.4 end devices while transmitting WLAN packets.

Figure 6. Heterogeneous M2M access network architecture.

J. Sens. Actuator Netw. 2016, 5, 12 10 of 20

J. Sens. Actuator Netw. 2016, 5, 12 12 of 21 Figure 5. Spectrum allocation of IEEE 802.15.4 and IEEE 802.11b networking standards.

TheThe proposedproposed heterogeneousheterogeneous networknetwork architecturearchitecture isis shownshown inin FigureFigure6 6.. The The network network is is made made up up ofof MM sensor nodes nodes divided divided into into NN clustersclusters where where P (PP (P= M/N) = M/N) is theis thenumber number of nodes of nodes supported supported by each by eachof the of 6LoWPAN the 6LoWPAN routers routers acting acting as the as head the headof each of cluster. each cluster. The 6LoWPAN The 6LoWPAN routers routers interface interface to a multi to a- multi-frequencyfrequency dual-r dual-radioadio router router (MFDRR) (MFDRR) gateway gateway using using 6LoWPAN 6LoWPAN interfaces. interfaces. The MFDRR The MFDRR accepts accepts data datafrom from the 6LoWPAN the 6LoWPAN routers, routers, aggregates aggregates data blocks data blocks,, and transmits and transmits them themto a data to a sink data using sink usingan 802.11 an 802.11link. This link. unique This unique MFDRR MFDRR architecture architecture has been has developed been developed to avoid to the avoid coexistence the coexistence problem. problem. As the Asname the namesuggests, suggests, the MFDRR the MFDRR can cansupport support multiple multiple channels channels to to accept accept data data from from different 802.15.4 802.15.4 clusters.clusters. InIn thisthis network,network, differentdifferent channelschannels areare usedused byby neighboringneighboring clustersclusters toto avoidavoid mutualmutual clustercluster interferences.interferences. Hence,Hence, toto accommodateaccommodate densedense networkingnetworking environments,environments, multiplemultiple 6LoWPAN6LoWPAN radioradio interfacesinterfaces are used at at the the MFDRR MFDRR tuned tuned to to different different carrier carrier frequencies. frequencies. In Figure In Figure 6, red6, red clusters clusters use useone onecarrier carrier frequency frequency while while the thegreen green clusters clusters use usea non a non-overlapping-overlapping different different carrier carrier frequency. frequency. As Asshown shown in inthe the figure, ﬁgure, the the neighboring neighboring clusters clusters will will avoid avoid interference interference due due to to use use of alternating carrier frequencies.frequencies. Additionally,Additionally the, the transmission transmission power power of endof end devices devices is limited is limited such such that packetsthat packets can only can beonly received be received by the by local the cluster local clusterheads. Hence,heads. Hence,by using by alternating using alternating carrier frequencies carrier frequencies and limiting and transmissionlimiting transmission power, inter-cluster power, inter interference-cluster interference can be avoided. can be The avoided. red and The green red dotted and green circles dotted show thecircles transmission show the transmission distances of 802.15.4 distances end of devices802.15.4 and end the devices black and dotted the circlesblack dotted show the circles transmission show the distancetransmission of the distance 802.11 transmitter of the 802.11 in thetransmitter MFDRR. in It can the be MFDR easilyR. seenIt can that be the easily 802.11 seen transmitter that the 802.11 in the MFDRRtransmitter will in interfere the MFDRR with all will 802.15.4 interfere end with devices all while 802.15.4 transmitting end devices WLAN while packets. transmitting WLAN packets.

FigureFigure 6.6. HeterogeneousHeterogeneous M2MM2M accessaccess networknetwork architecture.architecture.

5.1. MFDRR Architecture The most important and novel component of the proposed M2M area network is the MFDRR, which aggregates data and extends the transmission range, as well as increases the throughput of the heterogeneous network. Figure7 shows the MFDRR protocol stack and the queue structure. As can be seen from the ﬁgure, the MFDRR consists of two types of protocol stacks: the 6LoWPAN stack on the left side and the 802.11 stack on the right side. The former is developed in accordance with IEEE 802.15.4 and RFC 4944 standards [25]. Two 6LoWPAN MAC layers and two physical interfaces are used to support two frequencies/channels as mentioned earlier. The 802.11 PHY and MAC layers J. Sens. Actuator Netw. 2016, 5, 12 11 of 20

J.the Sens. left Actuator side and Netw. the2016 802.11, 5, 12 stack on the right side. The former is developed in accordance with13 IEEE of 21 802.15.4 and RFC 4944 standards [25]. Two 6LoWPAN MAC layers and two physical interfaces are used to support two frequencies/channels as mentioned earlier. The 802.11 PHY and MAC layers are aredeveloped developed using using the theIEEE IEEE 802.11g 802.11g standard standard [26 [].26 A]. buffer A buffer is used is used to connect to connect the the appl applicationication layers layers of ofthe the two two protocol protocol stacks; stacks; the the 6LoWPAN 6LoWPAN packets packets are are stored stored in in the the buffer buffer for for the the payload payload aggregation. aggregation.

Figure 7.7. The MFDRR protocol stack.stack.

Data packet flow within the MFDRR is processed in the following manner: upon receiving an Data packet ﬂow within the MFDRR is processed in the following manner: upon receiving an end end device packet from a 6LoWPAN router, the MFDRR 6LoWPAN stack strips off its headers and device packet from a 6LoWPAN router, the MFDRR 6LoWPAN stack strips off its headers and hands hands over the payload to the application layer. Subsequently, the payload is stored in an aggregation over the payload to the application layer. Subsequently, the payload is stored in an aggregation buffer buffer where payloads from multiple packets are aggregated to generate a WLAN payload for further where payloads from multiple packets are aggregated to generate a WLAN payload for further transmission to the sink. Once the aggregation buffer length reaches a certain threshold value, the 802.11 transmission to the sink. Once the aggregation buffer length reaches a certain threshold value, application layer encapsulates multiple 6LoWPAN payloads and forwards the aggregated payload to the 802.11 application layer encapsulates multiple 6LoWPAN payloads and forwards the aggregated the 802.11 MAC layer. The MAC layer then immediately generates a Blank Burst (BB) control signal payload to the 802.11 MAC layer. The MAC layer then immediately generates a Blank Burst (BB) to initiate an 802.11 packet transmission. The following section describes the BB signaling algorithm control signal to initiate an 802.11 packet transmission. The following section describes the BB signaling and 802.11 packet transmission technique. algorithm and 802.11 packet transmission technique.

5.2.5.2. The Blank Burst Algorithm ItIt is possible possible to to transmit transmit WLAN WLAN packets packets and and 6LoWPAN 6LoWPAN packets packets simultaneously simultaneously in the in same the samearea. area.However, However, a WLAN a WLAN packet packet transmission transmission can adversely can adversely affect 6LoWPAN affect 6LoWPAN packet transmissions packet transmissions owing to owinginter-network to inter-network interference. interference. To tackle Tothis tackle issue, this we issue,introduce we introduce a silence o ar silenceblanking or period blanking that period suspends that suspendsthe 6LoWPAN the 6LoWPAN transmission transmission during a during WLAN a WLAN packet transmission packet transmission by using by a using cooperativ a cooperativee MAC technique. The Blank Burst (BB) algorithm enforces a silence period on 802.15.4 devices and routers, MAC technique. The Blank Burst (BB) algorithm enforces a silence period on 802.15.4 devices and thus, allowing the 802.11 transmitter to use the shared transmission channel in an interference free routers, thus, allowing the 802.11 transmitter to use the shared transmission channel in an interference mode. In order to inform the end devices of this silence period, the 6LoWPAN superframe beacon is free mode. In order to inform the end devices of this silence period, the 6LoWPAN superframe used where a BB signaling packet is inserted in the beacon field. We refer to this signaling mechanism beacon is used where a BB signaling packet is inserted in the beacon ﬁeld. We refer to this signaling mechanism as the Blank Burst (BB), which is generated and disseminated by the MFDRR. The BB packet transmission timing is shown in Figure8. J. Sens. Actuator Netw. 2016, 5, 12 12 of 20

J. Sens.as Actuator the B Netw.lank 2016Burst, 5 ,(BB), 12 which is generated and disseminated by the MFDRR. The BB packet14 of 21 transmission timing is shown in Figure 8.

FigureFigure 8. Blank8. Blank burst burst (BB) (BB) packetpacket transmission timing timing relationship. relationship.

When 6LoWPAN payloads arrive at the MFDRR’s aggregation buffer, these payloads are Whenaggregated 6LoWPAN into WLAN payloads packets. arriveOnce the at buffer the MFDRR’slength reaches aggregation a predefined buffer, threshold these value, payloads the BB are aggregatedcontrol signal into WLANis triggered packets. at time T1 Once as shown the bufferin Figure length 8. A blank reaches burst arequest predefined is launched threshold from the value, the BBWLAN control application signal is layer triggered which atis relayed time T1 toas the shown 6LoWPAN in Figure MAC8 layer. A blank as illustrated burst request in Figure is 7. launched The fromlength the WLAN of the silence application period layerTBB is calculated which is using relayed Equation to the (4) 6LoWPAN, and included MAC in the layer BB signal as illustrated packet. in FigureAt7 .this The point length of time, of the the silence 6LoWPAN period MACT BBlayeris calculatedsends a blank using burst Equation feedback (4),signal and to includedthe WLAN in the BB signalapplication packet. layer, At indicating this point that of the time, 6LoWPAN the 6LoWPAN MAC layer MAC is transmitting layer sends the BB a blanksignal to burst end users feedback signalin tothe the next WLAN superframe. application The BB signal layer, packet indicating is transmitted that the from 6LoWPAN the MFDRR MAC which layer is rela isyed transmitting by the 6LoWPAN routers to end devices. Upon receiving the BB signaling packet at time T2, end devices the BB signal to end users in the next superframe. The BB signal packet is transmitted from the move to sleep mode for the TBB duration. Meanwhile, the 6LoWPAN packets are aggregated into MFDRRWLAN which packets is relayed in the MFDRR by the 6LoWPANwhich, in turn routers, are transmitted to end devices. to the data Upon sink receiving at time T2 the. The BB 802.11 signaling packetinterface at time ofT2 the, end MFDRR devices uses move the CSMA/CA to sleep mode protocol for the usingTBB theduration. distributed Meanwhile, coordination the function 6LoWPAN packets(DCF are) to aggregated transmit WLAN into WLANpackets. packetsIn a single in MFDRR the MFDRR-based which,network, in the turn, 802.11 are packets transmitted will not to the dataexperience sink at time anyT2 collision. The 802.11 and, hence interface, they of will the be MFDRR transmitted uses with the a CSMA/CA minimum delay. protocol After using the the distributedcompletion coordination of this blank function burst (DCF) at time to transmit T3, the WLANend devices packets. wake In up a single and resumeMFDRR-based data packet network, the 802.11transmission packets. will not experience any collision and, hence, they will be transmitted with a minimum delay. After the completion푇퐵퐵 = 푁(푇퐷퐼퐹푆 of+ this푇푏푎푐푘표푓푓 blank_푚푖푛 burst+ 퐿푎푔푔 at+ time푇푆퐼퐹푆 +T3푇,퐴퐶퐾 the) end devices wake(4 up) and resume data packet transmission. Equation (4) is used to calculate the blank burst duration where the DCF technique is used to transmit WLAN packets using the CSMA/CA protocol. In Equation (4) TDIFS denotes the distributed T “ N T ` T ` L ` T ` T (4) interframe spacing (DIFSBB ); Tbackoff_minDIFS denotesbacko the f f _minimummin agg back-SIFSoff delay;ACK Lagg denotes one WLAN packet transmission time including´ headers and payload, and TSIFS denotes short¯ interframe spacing Equation(SIFS). TACK (4) represents is used tothe calculate acknowledgement the blank packe burstt transmission duration where delay. the N DCFdenote techniques the number is usedof to transmitWLAN WLAN packe packetsts transmitted using per the BB CSMA/CA duration. protocol. In Equation (4) TDIFS denotes the distributed interframe spacing (DIFS); Tbackoff_min denotes the minimum back-off delay; Lagg denotes one WLAN 6. Simulation Model and Results packet transmission time including headers and payload, and TSIFS denotes short interframe spacing (SIFS). TACKTo evaluaterepresents the theeffectiveness acknowledgement of the proposed packet algorithm, transmission a discrete delay. eventN-baseddenotes OPNET the numbermodel of WLANhas packets been developed transmitted to simulate per BB the duration. network architecture shown in Figure 6. The key element of this model is the MFDRR that relays packets to and from end devices to the data sink. Figure 9 shows the 6. SimulationOPNET model Model structure and Results of the MFDRR. The left side of the figure shows the implementation of the 6LoWPAN protocol stack. Currently no 6LoWPAN model exists in the OPNET library, so we have To evaluate the effectiveness of the proposed algorithm, a discrete event-based OPNET model developed a new 6LoWPAN OPNET model. The 6LoWPAN protocol stack has been developed has beenutilizing developed the open to-zb simulate model available the network publicly architecture [27]. The open shown-zb inmodel Figure implements6. The key the element PHY and of this modelMAC is the layers MFDRR of the that IEEE relays 802.15.4 packets slotted to CSMA/CA and from protocol end devices. The to adaptation the data layer sink. developed Figure9 showsis the OPNETresponsible model for the structure IPv6 header of the compression MFDRR. Theand leftde-compression side of the as figure required shows by RFC the implementation4944. The IP of theand 6LoWPAN application protocollayers are stack.implemented Currently on top no of the 6LoWPAN adaptation model layer. The exists application in the OPNETlayer of the library, so weMFDRR have developedis split into two a new parts 6LoWPAN where the 6LoWPAN OPNET model. protocol The forwards 6LoWPAN payloads protocol to the aggregation stack has been developed utilizing the open-zb model available publicly [27]. The open-zb model implements the PHY and MAC layers of the IEEE 802.15.4 slotted CSMA/CA protocol. The adaptation layer developed is responsible for the IPv6 header compression and de-compression as required by RFC 4944. The IP and application layers are implemented on top of the adaptation layer. The application layer of the MFDRR is split into two parts where the 6LoWPAN protocol forwards payloads to the aggregation buffer which is used to generate 802.11 packets. In the reverse direction, when a WLAN J. Sens. Actuator Netw. 2016, 5, 12 15 of 21 packet is received from the data sink, the 802.11 protocol stack strips all headers and delivers the combined payload to the 802.15.4 application layer. The combined payload is de-aggregated by the 6LoWPAN application layer and individual payloads are sequentially forwarded to the respective MAC layers for the downlink transmission. The 802.11 protocol stack was implemented using the OPNET library. The key simulation parameters are also listed in Table3. End devices are located 300 meters away from the coordinator. In the heterogeneous network, a three-hop transmission link is used, whereas six hops are used in the case of a comparative homogeneous network model when only 6LoWPAN nodes are employed. For the heterogeneous network, the MFDRR to the data sink uses a 6 Mbits/s link that significantly reduces the packet transmission time compensating for the packet aggregation delay introduced by the buffer.

Figure 9. OPNET modeler architecture of the proposed heterogeneous network.

Table 3. Key simulation parameters.

Parameter Value 802.11 and 6LoWPAN Tx Power 100 mW and 1 mW Simulation duration 10 s MFDRR to Data sink distance 150 m End device to the MFDRR 100 m M2M area network service area 0.196 sq. km M2M node density: Heterogeneous network 326 nodes/sq. km Homogeneous network 163 nodes/sq. km 6LoWPAN and 802.11 channel nos: 11,12 (6LoWPAN) and 1 (802.11) Path loss model Free space 802.15.4 packet size (bytes) 128 802.11 packet size (bytes) 1200 Superframe Order (SO) 3 Beacon Order (BO) 4 6LoWPAN data rate (kbps) 250 WLAN data rate (Mbps) 6 Aggregation factor 25 Blank burst duration TBB 2.7 ms End device packet inter-arrival time, 2, 1, 0.66, 0.5 exponentially distributed (sec) J. Sens. Actuator Netw. 2016, 5, 12 16 of 21

Performance Analysis

ThisJ. Sens. section Actuator Netw. evaluates 2016, 5, 12 the performance of the proposed M2M heterogeneous area network14 of 20 and the effectiveness of the proposed Blank Burst algorithm. Simulation results are used to compare the performancePerformance of twoAnalysis M2M area networks. Using simulation models, we evaluate the performance of the proposedThis algorithmsection evaluate by usings the performance the following of metrics:the proposed packet M2M success heterog rateeneous (PSR), area end-to-end network and delay, and thethe numbereffectiveness of collisions. of the proposed The PSR Blank is Burst defined algorithm. as the ratioSimulation of the results number are ofused packets to compare successfully the receivedperformance by the data of two sink M2M to area the networks. total number Using of simulation packets generatedmodels, we byevaluate the end the performance devices. The of first two metricsthe proposed are also algorithm used toby compareusing the thefollowing performance metrics: packet of homogeneous success rate (PSR and), heterogeneousend-to-end delay M2M, area networks.and the number of collisions. The PSR is defined as the ratio of the number of packets successfully Simulationreceived by the models data sink were to the used total to number obtain of results packets fromgenerated three by different the end devices. networking The first scenarios. two metrics are also used to compare the performance of homogeneous and heterogeneous M2M area In the first scenario, a homogeneous network is used where the network elements are 802.15.4 end networks. devices, routers, and a data sink node. Thirty-two end devices are used using four 6LoWPAN clusters. Simulation models were used to obtain results from three different networking scenarios. In the A six-hopfirst scenario network, a is homogeneous simulated that network has the is used same where end device the network to data elements sink transmission are 802.15.4 distanceend devices, used in the heterogeneousrouters, and a data network. sink node In the. Thirty second-twoscenario, end devices 64 are end used devices using are four used 6LoWPAN where clusters. a multi-frequency A six- heterogeneoushop network network is simulated architecture that has the is simulatedsame end device without to data implementing sink transmission the BB distance signaling used algorithm;in the this mayheterogeneous result in inter-domain network. In the (802.11/802.15.4) second scenario, 64 collisions. end devices In thisare used case, where once aa 6LoWPANmulti-frequency payload arrivesheterogeneous at the buffer, network immediately architecture a WLAN is simulated packet without is generated implementing and transmitted the BB signaling using the algorithm; CSMA/CA protocolthis withoutmay result the in BBinter algorithm.-domain (802.11/802.15.4) In the third collisions scenario,. In 6LoWPAN this case, once payloads a 6LoWPAN are aggregated payload to generatearrives a WLANat the buffe packetr, immediately using a preseta WLAN aggregation packet is generated factor. and Once transmitted a WLAN using packet the CSMA/CA is generated, protocol without the BB algorithm. In the third scenario, 6LoWPAN payloads are aggregated to the BB signal is used to transmit the packet in an interference-free mode. generate a WLAN packet using a preset aggregation factor. Once a WLAN packet is generated, the Figure 10 shows the packet success rate of the three networking scenarios and demonstrates the BB signal is used to transmit the packet in an interference-free mode. marked differencesFigure 10 shows in PSR the values packet among success these rate of three the three scenarios. networking The PSR scenarios of the and heterogeneous demonstrates networkthe with themarked BB signaling differences (scenario in PSR values 3) algorithm among these decreases three scenarios. gradually The with PSR theof the offered heterogeneous load; where network the PSR dropswith from the 97% BB signaling to 53%. (scenario The PSR 3) value algorithm of the decreases heterogeneous gradually with network the offered (scenario load; 2)where without the PSR the BB algorithmdrops drops from 97% from to 75% 53%. to The 30% PSR with value the of increasing the heterogeneous load. The network homogeneous (scenario 2) network without (scenario the BB 1) experiencesalgorithm the drops lowest from PSR 75% whose to 30% value with reducesthe increasing from 48%load. toThe 8%. homogeneous The PSR value network for these(scenario networks 1) dependsexperiences on the the total lowest number PSR whose of collisions value reduces and network from 48% congestion to 8%. The levels.PSR value Figure for these 11 illustrates networks the link-by-linkdepends PSR on the rate total of thenumber homogeneous of collisions network.and network The congestion plot shows levels. that Figure the PSR11 illustrates value progressively the link- by-link PSR rate of the homogeneous network. The plot shows that the PSR value progressively decreases from the end devices mainly due to collisions and network congestion. As more packets decreases from the end devices mainly due to collisions and network congestion. As more packets are are accumulated in the routers, the network throughput decreases due to congestion and collisions. accumulated in the routers, the network throughput decreases due to congestion and collisions. AlthoughAlthough we havewe have used used a staggered a staggered link link design design toto avoid collisions collisions between between neighboring neighboring 6LoWPAN 6LoWPAN clustersclusters in the in multi-hop the multi-hop network, network, the the congestion congestion level level increases increases non-linearly non-linearly withwith the load load due due to to the use ofthe the use CSMA/CA of the CSMA/CA protocol. protocol. For limiting For limiting the paperthe paper size size we we are are not not describing describing the the staggered staggered link designlink which design can which be found can be in found [28]. in [28].

120%

100%

80%

60%

40% Packet success success Packet rate 20% Scenario 3 Scenario 2 Scenario 1 0% 0.5 0.7 0.9 1.1 1.3 1.5 1.7 1.9 2.1

End device packet inter-arrival rate (packet/sec)

FigureFigure 10. Packet10. Packet success success rate rate (PSR) (PSR) for for three three simulationsimulation scenarios for for different different offered offered load load conditions conditions..

J. Sens. Actuator Netw. 2016, 5, 12 15 of 20 J. Sens. Actuator Netw. 2016, 5, 12 17 of 21

60%

50%

40%

30% Packet rate success Packet

20%

10%

0% 0.5 0.7 0.9 1.1 1.3 1.5 1.7 1.9 2.1 End device packet inter-arrival rate (packet/sec) hop 1 hop 2 hop 3 hop 4 hop 5 hop 6

FigureFigure 11. 11Link-by-link. Link-by-link packet packet success success rate rate of of the the simulated simulated homogeneous homogeneous network. network.

ComparingComparing the the PSR PSR values values of of the the heterogeneous heterogeneous network network with with and and without without the the BB BB signaling signaling algorithmalgorithm shows shows that that the the BB BB signaling signaling algorithm algorithm significantly significantly increases increases the the throughput. throughput. Improved Improved performanceperformance is is achieved achieved due due to to the the absence absence of of inter-network inter-network collisions collisions and and lower lower network network congestion. congestion. TheThe heterogeneous heterogeneous network network has has the the advantage advantage of of fewer fewer hops, hops as, as well well as as a higha high data data rate rate MFDRR MFDRR to to the the datadata sink sink link. link. In In this this simulation, simulation, a 6a Mbits/s6 Mbits/s MFDRR MFDRR to to the the data data sink sink link link was was used. used. Figure Figure 12 12 shows shows packetpacket loss loss rates rates for for all all network network simulation simulation scenarios. scenarios. Packets Packets are are dropped dropped when when the the retransmission retransmission thresholdthreshold is is exceeded exceeded after after multiple multiple collisions; collisions; in in this this simulation, simulation, a retransmissiona retransmission threshold threshold of of four four waswas used. used For. For the the homogeneous homogeneous network, network, the the packet packet drop drop rate rate is is always always high high and and remains remains steady steady duedue to to lower lower network network capacity capacity andand congestion;congestion; recall recall this this scenario scenario also also experiences experiences the the lowest lowest PSR. PSR. The Theplot plot shows shows the the significant significant improvement improvement of of the the heterogeneous network network performance performance when when the the BB BB signalingsignaling is is used. used. As As shown shown inin thethe figurefigure forfor scenarioscenario 33 withwith traffictraffic load up to 1.5 packets/s packets/s/node,/node, the theoverall overall packet packet loss loss rate rate remains remains very very low. low. Compared Compared to scenario to scenario 3, scenario 3, scenario 2 results 2 results in a much in a much higher higherpacket packet loss rate loss even rate at even low network at low network traffic loads. traffic In loads.the heterogeneous In the heterogeneous network when network BB signaling when BBis signalingnot used, then is not both used, intra then and bothinter intranetwork and collisions inter network increase collisions due to the increase mutual dueinterference to the mutual between interferencedata packets between as well dataas interference packets as between well as interferencedata and ACK between packets. data Results and ACKclearly packets. show th Resultsat packet clearlyloss rate show increases that packet exponentially loss rate increases with incoming exponentially traffic without with incoming the BB signaling. traffic without The proposed the BB signaling. signaling Themechanism proposed signalingoffers significant mechanism QoS offers gain significantby using the QoS cooperative gain by using MAC the cooperativeprotocol, which MAC allows protocol, the whichsharing allows of the the transmission sharing of the channel transmission in a fair channel non-collision in a fair non-collisionmode. In heterogeneous mode. In heterogeneous networks, one networks,must consider one must the transmission consider the ranges transmission of the two ranges different of the networks. two different The 802.11 networks. transmitter The covers 802.11 a transmitterlonger transmission covers a longer range, transmission as well as transmits range, asat wella higher as transmits transmission at a higherpower, transmission compared to power,802.15.4 compareddevices. Hence, to 802.15.4 any 802.11 devices. packet Hence, could any collide 802.11 with packet a large could number collide of with end adevice large numberpackets when of end an deviceomnidirectional packets when antenna an omnidirectional is used in the MFDRR. antenna isUse used of the in the uniquely MFDRR.-proposed Use of theBB uniquely-proposedsignaling completely BBelim signalinginates the completely inter-network eliminates collisions. the inter-network collisions. End-to-endEnd-to-end delay delay plays play as significanta significant role role in in evaluating evaluating network network performance. performance. Figure Figure 13 13 shows shows thethe end-to-end end-to-end packet packet delay delay for for the the three three simulation simulation scenarios. scenarios. The The plot plot shows shows that that the the homogeneous homogeneous networknetwork introduces introduces very very high high packet packet delay delay due due to to the the higher higher number number of of collisions collisions and and network network congestioncongestion in in a a multi-hop multi-hop network. network. Simulation Simulation resultsresults showshow thatthat thethe largestlargest component of the the delay delay is isthe the queuing queuing delay at the the router router due due to to the the congestion. congestion. Comparing Comparing the the delay delay of of the the heterogeneous heterogeneous network,network, it it can can be be seenseen thatthat thethe heterogeneous ne networktwork without without the the packet packet aggregation aggregation and and the the BB signaling offers a lower delay at a low offered load, but the delay increases significantly as the load

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BBJ. Sens. signaling Actuator offers Netw. 2016 a lower, 5, 12 delay at a low offered load, but the delay increases signiﬁcantly as16 the of 20 load increases. One of the reasons for the lower delay is the shorter queuing delay because packet aggregationincreases. is One not of used. the However, reasons for this the advantage lower delaydiminishes is the as shorter the load queuing increases delay due to because high collision packet rates.aggregatio On then otheris not hand,used. However, the network this with advantage BB signaling diminishes maintains as the load a stable increases end-to-end due to delay high collision for all loadrates. conditions. On the other At hand, low trafﬁc the network load, thewith delay BB signaling is higher maintains compared a stable to scenario end-to- 2end due delay to the for longer all load waitconditions. period causedAt low traffic by the load, BB signal the delay propagation is higher comp delay.ared Over to scenario the multihop 2 due to network, the longer the wait MFDRR period needscaused to by wait the several BB signal superframe propagation periods delay. to allowOver the the multihop BB packets network, to propagate the MFDRR to all endneeds devices. to wait Onseveral the other superframe hand, at periods higher load,to allow the the scenario BB packets 3 delay to ispropagate lower compared to all end to devices. scenario On 2 due the toother absence hand, ofat interdomain higher load, collisions. the scenario The 3 end-to-enddelay is lower packet compared delay forto scenario an N hop 2 due network to absence using theof interdomain proposed heterogeneouscollisions. The network end-to-end can be packet expressed delay by for Equation an N hop (5) networkwhere T a,i usingis the the link proposed access delay, heterogeneousTQ is the queuingnetwork delay can be at expressed the router, byTagg Equationis the packet (5) where aggregation Ta,i is the delaylink access at the delay, MFDRR, TQ is and theT queuingBB is the delay blank at burstthe router, delay whichTagg is the absorbs packet the aggregation WLAN packet delay transmission at the MFDRR, time. and A T higherBB is the packet blank arrival burst delay rate could which increaseabsorbs the the total WLAN access packet delay transmission in the 6LoWPAN time. clusters, A higher but packet this delay arrival is compensated rate could increase for by the the lower total aggregationaccess delay delay. in the Additionally, 6LoWPAN clusters, the BB signaling but this techniquedelay is compensated completely eliminatesfor by the thelower inter-domain aggregation collisions;delay. Additionally, hence, performance the BB signaling at higher loadtechnique is not completely affected by theeliminates co-existence the inter issue.-domain collisions; hence, performance at higher load is not affected by the co-existence issue. N N´1 푁 푁−1 Tee “ Ta,i ` TQ ` Tagg ` TBB (5) 푇 =i“∑ 푇 +i“ ∑ 푇 + 푇 + 푇 (5) 푒푒 ÿ1 푎,푖 ÿ1 푄 푎푔푔 퐵퐵 푖=1 푖=1

50%

40%

30%

20% Packet Loss Loss Packet Rate

10%

0% 0.5 0.7 0.9 1.1 1.3 1.5 1.7 1.9 2.1 Packet inter-arrival rate(pkt/sec) Scenario 1 Scenario 3 Scenario 2

FigureFigure 12. 12Packet. Packet loss loss rates rates due due to to collisions collisions in in heterogeneous heterogeneous and and homogeneous homogeneous networks. networks.

FigureFigure 14 14 shows shows the the BB BB signaling signaling frequency frequency for for different different aggregation aggregation factors factors at at the the highest highest consideredconsidered network network trafﬁc traffic load. load. The The results results show show that that end end devices devices are are enforced enforced into into the the sleep sleep state state betweenbetween 3.6 3.6 times/s times/s andand 4 times/s when when devices devices cannot cannot transmit transmit any any packets. packets. In this In this simulation, simulation, a 2.7 ams 2.7 BB ms duration BB duration is used. is used. In this In case, this case, end devices end devices remain remain silent silent for a formaximum a maximum of 10.8 of ms/s. 10.8 ms/s.Use of Usesilent of silentperiods periods does doesnot affect not affect the cluster the cluster throughput throughput for two for tworeasons: reasons: first, ﬁrst, the silent the silent period period is very is verysmall, small, a maxim a maximumum of 10.8 of 10.8ms/s; ms/s; secondly, secondly, due to due the tostaggered the staggered link design, link design, some of some the silent of the duration silent durationwill overlap will overlap with the with sleep the period sleep periodof superframes of superframes of different of different links. links.From Fromsimulation simulation results, results, it was itfound was found that the that average the average cluster cluster throughput throughput is 12.4 is packets/s 12.4 packets/s and 12.3 and packets/s 12.3 packets/s for the forno theBB noand BB the andBB the scenarios BB scenarios respectively. respectively. Results Results indicate indicate that that the the BB BB signaling signaling improves improves the overall overall network network throughput and QoS by reducing inter-domain collisions, whereas cluster throughputs from end devices are not affected by the signaling technique.

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J. Sens.J. Sens.Actuator Actuator Netw. Netw. 2016, 20165, 12, 5, 12 17 of 1720 of 20 throughput and QoS by reducing inter-domain collisions, whereas cluster throughputs from end devices are not affected by the signaling technique.

100 100

10 10

Delay (sec) Delay Delay (sec) Delay 1 1

0.1 0.1 0.5 0.5 1 1 1.5 1.5 2 2 End deviceEnd device packet packet inter -interarrival-arrival rate (packet/sec)rate (packet/sec)

ScenarioScenario 1 1 Scenario Scenario 2 2 ScenarioScenario 3 3

FigureFigureFigure 13 13.. End End-to-end13.- Endto-end-to -delayend delay delay for for three threefor three different different different networking networking networking scenario. scenario. scenario.

4.2 4.2

4 4

3.8 3.8

3.6 3.6

3.4 3.4 3.2

BB frequency /sec) (BB frequency BB 3.2 BB frequency /sec) (BB frequency BB

3 3 5 5 10 10 15 15 20 20 25 25 AggregationAggregation Factor Factor

Figure 14. Blank Burst signaling frequency for different aggregation factors at a traffic load Figure 14. Blank Burst signaling frequency for different aggregation factors at a traffic load of of 2Figure packets/s/device. 14. Blank Burst signaling frequency for different aggregation factors at a traffic load of 2 packets/s2 packets/s/device./device. 7. Conclusions 7. Conclusions7. Conclusions This paper has presented a new cooperative MAC protocol for an M2M heterogeneous area This paper has presented a new cooperative MAC protocol for an M2M heterogeneous area networkThis to support paper IoT has applications presented a using new low-cost cooperative wireless MAC networking protocol for standards an M2M that heterogeneous operate in the area network to support IoT applications using low-cost wireless networking standards that operate in unlicensednetwork spectrum. to support The IoT work applications specifically using focused low on-cost eliminating wireless thenetworking inter-network standards collision that problem operate in the unlicensed spectrum. The work specifically focused on eliminating the inter-network collision to improvethe unlicensed the throughput spectrum. of anThe M2M work area specifically network infocused a dense on networking eliminating environment. the inter-network Simulation collision problem to improve the throughput of an M2M area network in a dense networking environment. resultsproblem show to that improve the proposed the throughput blank burst of signalingan M2M area algorithm network reduces in a dense the number networking of inter-network environment. Simulation results show that the proposed blank burst signaling algorithm reduces the number of collisionsSimulation significantly results andshow maintains that the aproposed stable delay blank profile. burst The signaling BB signaling algorithm structure reduces has nothe negative number of inter-network collisions significantly and maintains a stable delay profile. The BB signaling structure impactinter on-network the access collisions network’s significantly delay due and to maintains the introduction a stable ofdelay silence profile. periods. The BB The signaling BB signaling structure has no negative impact on the access network’s delay due to the introduction of silence periods. The BB architecturehas no negative improves impact the PSRon the value, access as network’s well as offers delay a stabledue to delaythe introduction and makes of the silence end-to-end periods. delay The BB signaling architecture improves the PSR value, as well as offers a stable delay and makes the end-to- lesssignaling dependent architecture on the traffic improves load. Thethe PSR BB signalingvalue, as well design as canoffers accommodate a stable delay different and makes traffic the QoSend-to- end delay less dependent on the traffic load. The BB signaling design can accommodate different traffic requirementsend delay less by adjustingdependent the on BBthe signalingtraffic load. period. The BB The signaling proposed design signaling can accommodate structure requiresdifferent notraffic QoS requirements by adjusting the BB signaling period. The proposed signaling structure requires no additionalQoS requirements signaling traffic by adjusting since the the BB signalBB signaling is propagated period. by The using proposed the beacon signaling field ofstructure the superframe. requires no additionaladditional signaling signaling traffic traffic since since the BB the signal BB signal is propagated is propagated by usin by using theg beacon the beacon field field of the of superframe. the superframe. The Thedesign design presente presented hered here is also is alsoscalable scalable where where both both networks networks can sharecan share the commonthe common transmission transmission spectrumspectrum without without intra intra- and- andinter inter-network-network collisions. collisions. The Theproposed proposed network network architecture architecture is suitable is suitable for afor dense a dense network network deployment deployment where where the frequency the frequency hopping hopping technique technique may may not benot useful be useful to avoid to avoid

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The design presented here is also scalable where both networks can share the common transmission spectrum without intra- and inter-network collisions. The proposed network architecture is suitable for a dense network deployment where the frequency hopping technique may not be useful to avoid inter-network collisions or interference. The proposed solution is also energy efficient compared to 3G/4G cellular networks since the short range networking standards use lower transmission power, as well as have lower signaling load. The developed BB signaling does not require any additional transmission resources as the BB signal is mapped onto the existing IEEE 802.15.4 superframes; hence, no additional transmission energy is necessary. It is well known that IEEE 802.15.4 networks are far more energy efficient than 4G/LTE networks [29]. The proposed heterogeneous network will maintain the same level of energy efficiency while providing M2M area networking support over a wide area. Other works have shown that cooperative MAC protocols in a random access network can improve the energy efficiency. [30] proposed a distributed information sharing (DISH) cooperative approach for a multichannel MAC to improve the energy efficiency. The proposed network will be further extended to incorporate multiple MFDRRs to support increased node density in a geographical area. Future research will also concentrate on the heterogeneous network architecture using the IEEE 802.11ah standard.

Author Contributions: J.Y.K. conceived the idea of a heterogeneous network architecture and the blank burst algorithm. D.C. implemented the idea and developed simulation models and obtained performance results. D.C. developed a unique OPNET simulation model to analyze the heterogeneous network performance. J.B. was involved in developing the simulation model and further enhanced the performance analysis model. Conﬂicts of Interest: The authors declare no conﬂict of interest.

References

1. OECD. Machine-to-Machine Communications: Connecting Billions of Devices; OECD Digital Economy Papers, No. 192; OECD Publishing: Paris, France, 2012. [CrossRef] 2. Wu, G.; Talwar, S.; Johnsson, K.; Himayat, N.; Johnson, N.D. M2M: From Mobile to Embedded Internet. IEEE Commun. Mag. 2011, 49, 36–43. 3. Polsonetti, C. Know the Difference between IoT and M2M. Available online: http://www.automationworld. com/cloud-computing/know-difference-between-iot-and-m2m (accessed on 27 July 2016). 4. Pereira, C.; Aguiar, A. Towards Efficient Mobile M2M Communications: Survey and Open Challenges. Sensors 2014, 14, 19582–19608. [CrossRef][PubMed] 5. Machine to Machine Communications (M2M): Functional Architecture; V2.1.1; ETSI: Sophia Antipolis, France, 2013. 6. Al-Fuqaha, A.; Khreishah, A.; Guizani, M.; Rayes, M.; Mohammadi, M. Toward Better Horizontal Integration Among IoT Services. IEEE Commun. Mag. 2015, 53, 72–79. [CrossRef] 7. Fan, Z.; Haines, R.J.; Kulkarni, P. M2M Communications for E-Health and Smart Grid: An Industry & Industry Perspective. IEEE Wirel. Commun. 2014, 19, 62–69. 8. Yu, R.; Zhang, Y.; Gjessing, S.; Xia, W.; Yang, K. Towards Cloud Based Vehicular Networks with Efficient Resource Management. IEEE Netw. 2013, 27, 48–55. [CrossRef] 9. Islam, M.T.; Taha, A.-E.M.; Akl, S. A Survey of Access Management Techniques in Machine Type Communications. IEEE Commun. Mag. 2014, 52, 74–81. [CrossRef] 10. Gartner Press Release, Gartner Says 6.4 Billion Connected “Things” will be in Use in 2016, Up 30 Percent from 2015. Available online: http://www.gartner.com/newsroom/id/3165317 (accessed on 27 July 2016). 11. Budka, K.C.; Deshpande, J.G.; Thottan, M. Communication Networks for Smart Grid; Springer: London, UK, 2014; pp. 186–189. 12. Khan, R.H.; Khan, J.Y. A comprehensive review of the application characteristics and traffic requirements of a smart grid communications network. Comput. Netw. 2013, 57, 825–845. [CrossRef] 13. Zanella, A.; Bui, N.; Castellani, A.; Vangelista, L.; Zorzi, M. Internet of Things for Smart Cities. IEEE Internet Things J. 2014, 1, 22–32. [CrossRef] 14. Gozalvez, J. New 3GPP Standard for IoT. IEEE Veh. Technol. Mag. 2016, 11, 14–20. [CrossRef] J. Sens. Actuator Netw. 2016, 5, 12 21 of 21

15. Banarjee, A. Efficient, Adaptive and Scalable Device Activation for M2M Communications. In Proceedings of the IEEE International Conferences on Sensing, Communications and Networking (SENCON) 2015, Seattle, WA, USA, 22–25 June 2015; pp. 399–407. 16. Brown, J.; Khan, J.Y. Key Performance Aspects of an LTE FDD Based Smart Grid Communications Network. Comput. Commun. 2013, 36, 551–561. [CrossRef] 17. Gutierrez, J.A.; Edgar, H.C.; Barrett, R.L. Low Rate Wireless Personal Area Network: Enabling Wireless Sensors with IEEE 802.15.4; Wiley-IEEE Press eBook: New York, NY, USA, 2007. 18. Rajandekar, A.; Sikdar, B. A Survey of MAC Layer Issues and Protocols for Machine to Machine Communication. IEEE Internet Things J. 2015, 2, 175–186. [CrossRef] 19. Park, M. IEEE 802.11ah: Sub-1-GHz License-Exempt Operation for the Internet of Things. IEEE Commun. Mag. 2015, 53, 145–151. [CrossRef] 20. Palattela, M.R. Standardized Protocol Stack for the Internet of (Important) Things. IEEE Commun. Surv. Tutor. 2012, 15, 1389–1406. [CrossRef] 21. Hui, J.W.; Culler, D.E. IPv6 in Low Power Wireless Networks. Proc. IEEE 2010, 98, 1865–1878. [CrossRef] 22. Torabi, N.; Rostamzadeh, K.; Leung, V.C.M. IEEE 802.15.4 Beaconing Strategy and the Coexistence Problem in ISM Band. IEEE Trans. Smart Grid 2015, 6, 1463–1472. [CrossRef] 23. Montenegro, G.; Kushalnagar, N.; Hui, J.; Culler, D. Transmission of IPv6 packets over IEEE 802.15.4 networks. Internet Proposed Stand. RFC 2007, 4944, 2–8. 24. Hong, K.; Lee, S.; Lee, K. Performance Improvement in ZigBee-based home networks with coexisting WLANs. Pervasive Mob. Comput. 2015, 19, 156–166. [CrossRef] 25. Han, S.; Zhang, X.; Shin, K. Fair and Efficient Coexistence of Heterogeneous Channel Widths in Next Generation Wireless LANs. IEEE Trans. Mob. Comput. 2016.[CrossRef] 26. Wireless LAN Medium Access Control (MAC) and Physcial Layer (PHY) Specification; IEEE Standard 802.11-2007; IEEE: New York, NY, USA, 2007. 27. Open-ZB. Open Source Toolset for IEEE 802.15.4 and ZigBee. Available online: http://www.open-zb.net (accessed on 27 July 2016). 28. Chen, D.; Brown, J.; Khan, J.Y. Performance Analysis of a Distributed 6LoWPAN Network for the Smart Grid Applications. In Proceedings of the IEEE ISSNIP, Singapore, 14–21 April 2014. 29. Abbas, Z.; Yoon, W. A Survey on Energy Conserving Mechanisms for the Internet of Things: Wireless Networking Aspects. Sensors 2015, 15, 24818–24847. [CrossRef][PubMed] 30. Luo, T.; Motani, M.; Srinivasan, V. Energy Efficient Strategies for Cooperative Multi-channel MAC protocols. IEEE Trans. Mob. Comput. 2012, 11, 553–566.

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