electronics Article MFVL HCCA: A Modified Fast-Vegas-LIA Hybrid Congestion Control Algorithm for MPTCP Traffic Flows in Multihomed Smart Gas IoT Networks Mumajjed Ul Mudassir 1,2,* and M. Iram Baig 2 1 Electrical and Computer Engineering Department, Air University, Islamabad 44000, Pakistan 2 Electrical Engineering Department, University of Engineering and Technology, Taxila 47050, Pakistan; [email protected] * Correspondence: [email protected] Abstract: Multihomed smart gas meters are Internet of Things (IoT) devices that transmit information wirelessly to a cloud or remote database via multiple network paths. The information is utilized by the smart gas grid for accurate load forecasting and several other important tasks. With the rapid growth in such smart IoT networks and data rates, reliable transport layer protocols with efficient congestion control algorithms are required. The small Transmission Control Protocol/Internet Protocol (TCP/IP) stacks designed for IoT devices still lack efficient congestion control schemes. Multipath transmission control protocol (MPTCP) based congestion control algorithms are among the recent research topics. Many coupled and uncoupled congestion control algorithms have been proposed by researchers. The default congestion control algorithm for MPTCP is coupled congestion control by using the linked- increases algorithm (LIA). In battery powered smart meters, packet retransmissions consume extra power and low goodput results in poor system performance. In this study, we propose a modified Citation: Mudassir, M.U.; Baig, M.I. Fast-Vegas-LIA hybrid congestion control algorithm (MFVL HCCA) for MPTCP by considering the MFVL HCCA: A Modified requirements of a smart gas grid. Our novel algorithm operates in uncoupled congestion control Fast-Vegas-LIA Hybrid Congestion mode as long as there is no shared bottleneck and switches to coupled congestion control mode Control Algorithm for MPTCP Traffic otherwise. We have presented the details of our proposed model and compared the simulation results Flows in Multihomed Smart Gas IoT Networks. Electronics 2021, 10, 711. with the default coupled congestion control for MPTCP. Our proposed algorithm in uncoupled mode https://doi.org/10.3390/ shows a decrease in packet loss up to 50% and increase in average goodput up to 30%. electronics10060711 Keywords: multipath TCP; Internet of Things; congestion control; smart gas meter; smart gas network Academic Editor: Seok-Joo Koh Received: 11 February 2021 Accepted: 10 March 2021 1. Introduction Published: 18 March 2021 The goal of the Internet of Things (IoT) is to connect different devices and sensors to the Internet. According to a prediction by the Statista research department, the number Publisher’s Note: MDPI stays neutral of active IoT-connected devices such as sensors, nodes, and gateways will reach up to with regard to jurisdictional claims in 30.9 billion units worldwide by 2025 [1]. Smart city is the new trend of the era and the published maps and institutional affil- IoT is playing a major role in the design and deployment of smart city infrastructure. The iations. design of a smart city is divided into multiple domains, subsystems, and blocks and it is really difficult to implement an efficient design for a smart city by using the IoT. Some of the important domains of a smart city are electricity and natural gas management, water management, irrigation, waste material, parking space, and intelligent street lighting [2,3]. Copyright: © 2021 by the authors. The datasets used in the design and simulation of such domains are publicly available on Licensee MDPI, Basel, Switzerland. the Internet [4,5]. This article is an open access article distributed under the terms and 1.1. Smart Gas Networks conditions of the Creative Commons All over the world, natural gas is being used in homes and industries for heating and Attribution (CC BY) license (https:// fueling purposes. Many research and development organizations are conducting their creativecommons.org/licenses/by/ 4.0/). research in the area of IoT-based smart grids for natural gas [6,7]. Gas utilities gather Electronics 2021, 10, 711. https://doi.org/10.3390/electronics10060711 https://www.mdpi.com/journal/electronics Electronics 2021, 10, 711 2 of 27 real-time data for load forecasts, efficient gas transportation, pressure gauging, gas theft detection, gas leaks, pipe corrosion, and remote cut off in emergency situations. To achieve this, communication networks with advanced infrastructure are required; smart meters and sensors use these networks for data transmission. All the components are connected to form a smart grid [8]. Once the network is established [9], data can be collected by gas utilities even from old non-smart gas meters by attaching some extra devices and sensors [10]. Then, the data is analyzed with the help of artificial intelligence software for further actions [11]. 1.2. Smart Gas Meters A smart gas meter is an IoT device that consists of a processing unit connected with different sensors, wireless communication modules, real-time clock, power management units, electric motors to control valves, display unit, and a battery [12]. In addition to measuring gas flow, it also wirelessly connects to a smart gas grid over wide area networks allowing data access, remote location monitoring, infrastructure maintenance, automatic billing, and load forecasting [13]. It can request a remote gas cut-off after detecting emergency situations by sensing earthquakes, gas leakage, etc. Batteries are used as the power source for smart meters. Low power modules are preferred in the design of a smart meter to enhance battery life [14]. Multiple wireless interface standards can be used in a smart meter design to enable it to simultaneously connect to multiple heterogeneous or homogeneous networks. 1.3. Selection of Appropriate Protocol in an IoT Network The Internet runs on hundreds of protocols; many protocols are supported by IoT and many are still under development. When designing an IoT system, the system requirements should be defined very precisely, and then the right protocol should be chosen to address them. Currently, due to an increase in memory size and processing power, small, embedded devices and modules are capable of running large programs and algorithms. Development of new wireless communication standards such as IEEE 802.11 ah (Wi-Fi Halow) for IoT have also enabled the devices to communicate at much higher data rates over long distances [15,16]. In any communication network with many devices, network congestion is the main issue that causes poor data rates and packet loss [17]. In the IoT, Transmission Control Protocol (TCP) has traditionally been avoided as a transport-layer protocol due to the extra overhead associated with it. However, recent trends and developments in IoT devices and networks are favoring TCP for congestion control and end-to-end reliable delivery of data [18]. 1.4. Multipath Transmission Control Protocol (MPTCP) in Multihomed Devices Modern IoT devices are equipped with multiple network interfaces, capable of simulta- neously connecting to multiple network links and different Internet Protocol (IP) addresses. These links can be used for concurrent transfer of data, then if any links fail others can be used for successful data delivery. The multipath transmission control protocol (MPTCP) is embedded in all such modern multihomed devices. Multihoming is defined as the ability of a host or device to simultaneously connect to multiple heterogeneous or homogeneous networks [19]. Multihomed devices with MPTCP protocol support, divide the application’s data into multiple streams, and then utilize multiple network paths simultaneously for data transmission/reception. Load balancing, congestion control, and dynamic switching are handled by the protocol in order the improve throughput and quality of service [20]. 1.5. Smart Gas Grid Infrastructure In Figure1, we present the structure of an IoT-based smart natural gas grid that uses multihomed smart gas meters with dual low power Wi-Fi Halow interfaces capable of simultaneously connecting to two gateways of different Internet service providers (ISPs) for parallel transfer of data to server. The information received from these smart meters, and Electronics 2021, 10, x FOR PEER REVIEW 3 of 28 1.5. Smart Gas Grid Infrastructure In Figure 1, we present the structure of an IoT-based smart natural gas grid that uses multihomed smart gas meters with dual low power Wi-Fi Halow interfaces capable of Electronics 2021, 10, 711 3 of 27 simultaneously connecting to two gateways of different Internet service providers (ISPs) for parallel transfer of data to server. The information received from these smart meters, and from some other data sources, for example, weather information, is then used by the fromsmart some grid otherfor short-term data sources, load forforecasting example, (STFL). weather Deep information, learning ismethods then used are by used the for smart ac- gridcurate for load short-term forecasts. load Gas forecasting distribution (STFL). management Deep learning makes methods decisions are usedaccording for accurate to the loadforecasts forecasts. for intelligent Gas distribution distribution management of gas to different makes decisions areas. In accordingsuch IoT networks to the forecasts where forend-to-end intelligent reliable distribution transmission of gas toof differentdata from areas. smart In meters such IoT to networksa server is where required, end-to-end