MQTT-RD: a MQTT Based Resource Discovery for Machine to Machine Communication

MQTT-RD: A MQTT based Resource Discovery for Machine to Machine Communication Eliseu Pereira, Rui Pinto, Joao˜ Reis and Gil Gonçalves SYSTEC - Research Center for Systems and Technologies, Faculty of Engineering, University of Porto, Porto, Portugal Keywords: M2M Communication, IoT, Resource Discovery, Resource Directory, Zero Configuration, MQTT. Abstract: The Internet of Things (IoT) is one of the key enablers for digital businesses and economic growth. By in- terconnecting objects and people through diverse heterogeneous networks, using Machine to Machine (M2M) communication, IoT enables the continuous monitoring of devices its surrounding environment, proving to have a huge potential in terms of new business opportunities. One of the biggest challenges nowadays in M2M communication, is the way devices are capable to look up for other devices and their services in local networks and internet. This paper proposes a distributed resource discovery architecture (MQTT-RD) based on the MQTT protocol. The proposed architecture enables decentralized discovery and management of devices in multiple networks, by introducing plug and play capabilities to devices, contributing for a mechanism for zero-configuration networking in IoT environments. This architecture was tested in an experimental environment, composed of multiple devices, in order to test resource discovery capabilities using an MQTT based protocol. The evaluated metrics were the overall message drop in the network, the delays in the delivery of messages and the processing time of each message. 1 INTRODUCTION extended the definition of CPS by mentioning the im- portance of networking, control-loops and distribu- Information and Communication Technology (ICT) is tion. In fact, CPS differ of embedded systems in the considered to be one of the most important areas dur- sense that CPS operate in a much larger scale, while ing the last decades and upcoming years. The con- an embedded system is a self-contained system con- stant miniaturization of technology enabled informa- fined to a single device. CPS usually include many tion processing devices to shift from large comput- embedded systems and other devices. ers towards small portable computers integrated into The electronics of a CPS are controlled based on larger products. ICT devices embedded into larger an open control feedback loop, where the resulting systems led to the term ‘embedded systems’. These sensor information of the physical process monitoring systems are defined as information processing sys- is used to control and optimize the CPS functionality. tems embedded into enclosing products, character- In a CPS, sensors and actuators have been recently ized specially for their real-time constrains, depend- enabled by Wireless Sensor and Actuator Networks ability, concurrency and efficiency requirements. (WSAN). Sensors perceive the environment condi- These embedded systems have been equipped tions of the physical world and these data is used as with sophisticated sensors and actuators, interfaces, input in decision making processes. These processes processors, complex control loops, software agents are usually represented as holonic representations of and communication means. Since the embedded com- the physical object in the virtual world, mostly known putation on these products uses closed models and as Digital Twins (DT). Usually, in a CPS, several algorithms to control the electronics, the link to the components of the system are represented by several physical world is frequently ignored. More recently DTs. Because centralized control is unsuitable for this close link between computation and real world large-scale system integration, cooperation between has recently been stressed by the introduction of the networked DTs enables distributed control. term Cyber-Physical Systems (CPS). [Lee, 2008] de- Advances in wireless technology enabled the ex- fined CPS as the integration of computation and phys- tension of devices with network connectivity for re- ical processes. Later, [Hellinger and Seeger, 2011] mote monitoring and control. These solutions based 115 Pereira, E., Pinto, R., Reis, J. and Gonçalves, G. MQTT-RD: A MQTT based Resource Discovery for Machine to Machine Communication. DOI: 10.5220/0007716201150124 In Proceedings of the 4th International Conference on Internet of Things, Big Data and Security (IoTBDS 2019), pages 115-124 ISBN: 978-989-758-369-8 Copyright c 2019 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved IoTBDS 2019 - 4th International Conference on Internet of Things, Big Data and Security on communication between devices, also know as challenges, namely [Song et al., 2014,Datta and Bon- Machine to Machine (M2M) communication [Galetic´ net, 2015]: 1) Communication interoperability, due et al., 2011], were based on closed networks, built to the heterogeneity of the communication technolo- specifically for this purpose. Later, this network con- gies used by different devices, e.g., Bluetooth, Zig- nection was based on the Internet Protocol (IP), al- bee, Modbus, etc; 2) Semantic interoperability, due to lowing for IP enabled devices to be monitored and different data models used to exchange sensor mea- controlled over the Internet. Connecting objects to surements and actuator commands; 3) Resource dis- each other over the Internet is the main idea of the covery, i.e., lack of capabilities to detect devices and Internet of Things (IoT). services offered by these devices in a CPS or IoT envi- The term IoT refers to uniquely identifiable phys- ronment, e.g., sensor measurements and/or actuation ical objects (‘Things’), also known as Smart Objects, commands; 4) Self-management, i.e., lack of system and their virtual representations in an internet-like capabilities to configure network topology and man- structure, namely the DT. The internet represents the age a large number of smart devices across multiple global networking of connected Smart Objects, en- networks. abling them to communicate with each other by ex- Several M2M architectures were developed by changing and transforming information. [Gubbi et al., different standard organizations to tackle some of 2013] define IoT as the interconnection of sensing and these challenges, such as the European Telecommuni- actuation devices, providing the ability to share in- cations Standards Institute (ETSI) [Boswarthick and formation across platforms through a unified frame- Mulligan, 2009], 3rd Generation Partnership Project work, developing a common operating picture for en- (3GPP) [Kunz et al., 2012] and one Machine to Ma- abling innovative applications. It represents informa- chine (oneM2M) [Chang et al., 2011]. In this pa- tion, networking and knowledge being integrated into per, the authors tackle the resource discovery chal- CPS. lenge, by proposing a distributed resource discov- IoT networks have several applications, at the ery approach, which enables zero-configuration net- level of factories, hospitals, cities or agriculture. working in an IoT environment. This approach in- Within Industrial IoT applications, M2M communica- troduces to M2M networked devices capabilities to tion enables full automation of sensors and actuators, discover other devices and services in the same lo- allowing machines to be interconnected and to com- cal network and in remote networks, without relying municate over a network with minimal human inter- in a centralized entity to manage devices and com- vention. Human operators and stakeholders are able munications. The proposed solution, named MQTT- to access production systems and monitoring man- RD, explores the MQTT protocol by using the Con- ufacturing processes, using several Human-Machine strained RESTful Environments Resource Directory Interfaces (HMI) and remotely connected devices. (CoRE RD) principles. To validate the proposed so- This enables the collection of machine condition and lution, scalability tests were carried out in an exper- diagnosis data, and control process parameters for op- imental environment. The experimental environment timizing costs and product quality. Also, M2M com- contains 2 machines, one runs the main component of munication enables machines to connect with the IT the MQTT-RD (Sniffer) while the other machine sim- infrastructure of their own manufactures, in order to ulates multiple devices, which are successively added request repairs and order new parts and components. to the network. Through the scalability tests it is pos- Regarding Intelligent Transportation Systems, sible to infer about the overall message drop in the M2M will play an important role in connecting cars, network, the delays in communication between com- buses, traffic lights, trams, roads and emergency ponents and the processing time of new messages by crews, enabling the interconnection of all objects and the Sniffer. From these metrics is estimated the limit roads for road traffic efficiency and safety. In e- number of devices per Sniffer, and when this limit is Healthcare applications, patients staying at home with reached, Sniffer overloads message management, i.e, medical bio-sensors can be monitored remotely by at this point Sniffer can only receive messages, not doctors in the hospital, collecting data and analyzing being able to forward them to the subscribers devices. the patient’s health condition in real time. Networked The rest of the paper is organized as follows. Sec- smart meters and advanced metering infrastructures tion 2 presents the background and surveys the state-

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