AODV routing protocol for Cognitive radio access based Internet of Things (IoT)
Introduction
Enhanced radio access networking technologies are proposed to integrate in next-generation radio communication systems to improve their resilience, efficiency, adaptability, and sustainability [1]. Due to this, a tremendous interest in enabling the concepts of Internet-of-Things (IoT) will be accomplished where thousands of constrained devices (sensors, actuators) are going to interact with their environments and inter-networked together and accessible through the internet to connect with non-constrained networks. In order to provide interoperability among existing proprietary based constrained IoT networks and enable internetworking with external networks, IETF (Internet Engineering Task Force) developed an open standardization protocol stack for LLN networks (IoT) through IP-based connectivity. Currently, 6LoWPAN is the proposed standard to translate the IP datagram to MAC frame through compression and fragmentation. The design of constrained routing protocol plays a significant role in improving the performance of the constrained IoT network with minimal node energy consumption. To achieve, IETF propose a proactive based IPv6 distance vector routing protocol for Low-power and Lossy Networks (RPL). Constrained nodes(Sensors, actuators and constrained boarder routers) within the IoT network that are running RPL protocol are connected by constructing a Destination Oriented Directed Acyclic Graph (DODAG). Root node (LLN boarder router) initiates the DIO(DODAG Information Object) control messages with metric container options to form a DODAG for specific instance. With this, LLN nodes within the constrained network is able to select its parent node (best candidate of intermediate node) within a set of next-hop neighbors (called parent set, parent list) to forward the constrained application data from leaf node to LBR(LLN boarder router). Later, LBR can either send the constrained application data back to the LLN network or send it to external non-constrained network. In general, wired/wireless (WiFi, WiMAX) network is used to transmit the constrained data from one constrained IoT network(LBR) to other constrained network(LBR) or from constrained IoT network(LBR) to non-constrained network (external networks). Broadband Wireless Access (BWA) can be an attractive solution for the network operators to transmit the constrained IoT data in between different LLN networks or from LLN network to non-constrained network (see Fig. 1). This is because of reduced installation cost and easy deployment of wireless networks. State-of-the-art research briefly explored that the existing radio technologies (WLAN’s, PAN, Sensor Networks) operating in unlicensed ISM(Industrial, Scientific and Medical) spectrum bands (2.4 GHz, 5 GHz) results in heavy spectral congestion that leads to severe spectrum scarcity. On the other hand, National Telecommunications and Information Administration (NTIA) spectrum regulatory framework describes that the spectrum allocated in most of the licensed frequency bands are underutilized due to static spectrum access by primary users which cannot be accessed by the secondary users [[2], [3], [4], [5]]. According to Federal Communications Commission, most of the allocated licensed spectrum band is used sporadically; and geographical variations in the usage of allocated spectrum with utilization ranging from 15% to 85% in the bands below 3 GHz. This clearly shows that the usage of licensed spectrum mainly depends on location and specific wireless technologies. Thus, spectrum scarcity is mainly due to the inadequate spectrum management polices instead of physical scarcity of its usage. One way to efficiently utilize the radio spectrum is by allowing the heterogeneous unlicensed radio services in static licensed spectrum band through dynamic spectrum access (DSA) and opportunistic channel access. With this, a new concept called “Cognitive Radio Technology” is evolved to efficiently reuse the underutilized licensed spectrum band by allowing secondary users to transmit its application data in licensed spectrum band (spectrum holes or white spaces) opportunistically without interrupting primary user’s communication. FCC has approved to transmit the unlicensed radio devices in “spectrum holes”, i.e., portions of the licensed TV bands that are not in active use by legitimate users, such as TV broadcasters [6]. This clearly shows that the opportunistic radio access based cognitive radio networking can be the lucent networking technology to alleviate the radio spectrum scarcity issue which is highly significant to accommodate the data for millions of IoT devices. In this work, Cognitive AODV routing protocol is proposed to discover the channel-route to transmit the constrained IoT data from LLN boarder to the non-constrained network (Cognitive radio networks) through the licensed PU free channels (TV spectrum bands). The rest of the paper is organized as follows. Section 2 briefly explains about the state-of-the-art research in routing protocol design for cognitive radio ad-hoc networks. Furthermore, the essence of interoperability in between IoT and Cognitive radio at the LBR is briefly explored to re-transmit the IoT-constrained data through opportunistic PU free licensed channels. Section 4 briefly explains about the proposed Directional-Cognitive hybrid CCC based AODV routing protocol along with the IPv6 encapsulation of IoT constrained data to transmit from one LBR to another LBR through cognitive radio network. Section 5 briefly explains about the experimental results that are analyzed with proposed directional hybrid-CCC-CR-AODV protocol and compared with existing In-band and out-of-band-CCC based CR routing protocols. Finally, Section 6 ends up with conclusion and future work.
Section snippets
Related work
Performance of Cognitive routing protocol mainly depends on achievable end-to-end throughput, end-to-end delay and node energy consumption at the network layer. To achieve this, Common Control Channel (CCC) [7] plays a pivotal role in establishing a synchronized control channel to setup directional end-to-end channel-path for IoT application data transmission opportunistically from LBR to the non-constrained networks. In addition, CR node density and number of simultaneous non-interfering
System model
CR-AODV routing protocol works under half duplex radio transceiver, i.e., a cognitive node can either transmit or receive the IoT data in the PU free communication channel. In addition, each Cognitive transceiver is equipped with ‘N’ directional antennas with an angle of ‘2 /N’ radians. In Fig. 3, antenna beams indexed are fixed and oriented in the same direction that cannot be changed with node mobility. Nodes(LBR’s) within the CR network are equipped with Global Position System (GPS)
Directional hybrid-CCC-CR-AODV
Whenever, the CR node(IoT boarder router) has IoT constrained data at network layer then it has to check for the destination channel-route in the routing table. In general, the sender needs to explore a new channel-route through RREQ/RREP to destination CR node in CCC whenever, destination routing entity does not exist in sender’s routing table. State-of-the-art CCC based CR-AODV protocol has certain limitations to select optimized energy efficient end-to-end channel-route due to longer channel
Simulation results
Discrete event driven based Network Simulator (NS-2.31) [[26], [27], [28], [29], [30], [31]] with cognitive radio capability is used to implement the proposed hybrid CCC based CR-AODV routing protocol with directional antennas. It is noteworthy that the IoT constrained data is transmitted from LLN boarder router (Source cognitive radio) to CR destination node. Furthermore, constrained IoT data is accumulated at the LLN boarder router to transmit it though multi-hop cognitive radio network.
Conclusion and future work
Common control channel at network layer in cognitive radio networks plays a significant role in selecting energy efficient end-to-end channel-route for IoT application data transmission from IoT gateway to cognitive backbone network. Moreover, link channel access delay, multi-channel hidden terminal due to inefficient node synchronization, cognitive and route control overhead has a direct impact on control channel design. With existing In-band or Out-of-band CCC-CR-AODV routing protocols, it is
Acknowledgments
The authors would like to thank the anonymous reviewers for their valuable comments and suggestions to enhance the quality of paper.
Satish Anamalamudi received the B.Eng. degree in Computer Science and Engineering from Jawaharlal Nehru Technological University, Hyderabad, India, M.Tech in Network and Internet Engineering from Karunya University, Coimbatore, India and Ph.D. in Communication and Information Systems from Dalian University of Technology, Dalian, China. He worked as a Research Engineer in Beijing Huawei Technologies, Beijing, China, from November 2015 to Jan, 2017. Currently, he is working as “Assistant
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Satish Anamalamudi received the B.Eng. degree in Computer Science and Engineering from Jawaharlal Nehru Technological University, Hyderabad, India, M.Tech in Network and Internet Engineering from Karunya University, Coimbatore, India and Ph.D. in Communication and Information Systems from Dalian University of Technology, Dalian, China. He worked as a Research Engineer in Beijing Huawei Technologies, Beijing, China, from November 2015 to Jan, 2017. Currently, he is working as “Assistant Professor” in “Faculty of Computer and Software Engineering”, Huaiyin Institute of Technology, Huaian, China. His research interests include common-control-channel design for MAC and routing protocols in cognitive radio ad hoc networks, MAC and routing protocol design of IoT and 5G networks.
Abdur Rashid Sangi served as Assistant Manager, I.T. in the public sector R&D, Karachi, Pakistan before Ph.D. He received a Bachelor’s degree in Computer Science and Engineering from Shah A. Latif University, Khairpur, Pakistan and his Master’s degree in Communication Networks from Bahria University, Karachi Campus, Pakistan. He was awarded with full-scholarship and finished his Ph.D. in Communication Network Security from Beijing University of Aeronautics and Astronautics (Beihang), China. Later he served as Software Engineer/Product Manager in Hisense International Co. Ltd, Qingdao, China and was a Senior Engineer in the Huawei R&D center, Beijing, China until August, 2017. Currently he is an Associate Professor in Huaiyin Institute of Technology, Jiangsu, China. His current research interests include IoT security, Contiki, 6LoWPAN and Routing protocol optimization and design.
Mohammed Alkatheiri is an Assistant Professor in the Department of Computer Science, College of Computing and Information Technology, University of Jeddah, Saudi Arabia. Currently, he is a chair of the Information Technology Department. His current research interest focuses on the area of information security. Previously, he worked as a researcher in the Center of Excellence in Information Assurance at the King Saud University, Riyadh, Saudi Arabia. His research interest focusing on security and privacy related issues of information sharing, identification, and authentication. Also, he served as consultant for national projects and joined Prince Muqrin Chair for Information Security Technology (PMC) along with government departments on National Information Security Strategy project as a security consultant.
Ahmedin Mohammed Ahmed (M’16) received his Ph.D. degree from Dalian University of Technology, Dalian, China in 2015, the Master’s degree in Software Engineering from Chongqing University, Chongqing, China, in 2011, and the B.S. degree in Computer Science from Bahirdar University, Bahirdar, Ethiopia, in 2006 . He is currently serving as Assistant Professor of Network and Software Engineering as well as Scientific Director (with the position of Vice-President) at Kombolcha Institute of Technology, Wollo University, Kombolcha, Ethiopia. He authored/co-authored 20+ research papers in reputable journals and conferences such as IEEE Transactions on Parallel and Distributed Systems, IEEE Transactions on Computers, IEEE Transactions on Vehicular Technology, IEEE Systems Journal, IEEE Access, Ah-hoc Networks, ACM WWW. He also co-authored one book chapter in his research area. In addition to the publications, he serves as invited reviewer for a number reputable and journals such as IEEE Systems Journal. He is contributing to the discipline by advising Masters level students in Ethiopian Universities such as Jimma University, Gondar University, etc. He is also co-advising Ph.D. candidates in Etho-France and Ethio-German Sandwich programs. His research interests include mobile and social computing, ad-hoc social networks, mobile data management, middleware design, software engineering, IoTs, big data and ERP.