Markov Chain-based Mobility Prediction and Relay-node Selection for QoS Provisioned Routing in Opportunistic Wireless Network

Abstract

In the fields of networking and communication, wireless sensor networks are a commonly used technology. Although Mobility in Wireless Networks or Mobile Ad hoc Networks (MANETs) were developed to solve most critical problems in a disaster scenario. However, data transmission in a disaster area is a difficult operation due to irregular connections between sensing devices and the sink. Opportunistic network-based MANETs are utilized to overcome this problem. There are many routing issues such as communication overhead ratio, packet loss, and packet delivery ratio at mobile nodes. There are several traditional approaches used in opportunistic networks for node localization and routing. The drawback of these traditional routing methods is their poor reliability. A Markov chain-based opportunistic routing protocol is proposed in this paper. A Markov chain model is used to predict the node mobility for the random mobility model, and a neighbor table-based relay node selection procedure is proposed. A Markov prediction model uses the history of a node’s movement without requiring additional information. By analyzing simulation metrics including delay, overhead rate, packet drop, and packet delivery rate, the proposed routing protocol is evaluated and verified based on the Packet Delivery Ratio (PDR) in an opportunistic network environment (ONE) simulator. In addition, existing routing protocols such as Spray and Wait (SNW), Epidemic, Prophet, and MaxPro differ from the proposed routing protocol in terms of buffer size, node count, and message generation rate. Corresponding result analysis demonstrates the superior performance of the proposed routing protocol over existing protocols.

KEYWORDS:

• Markov chain model
• Mobility prediction
• Opportunistic network
• Opportunistic network environment (ONE) simulator
• Relay node selection
• Transition probability matrix

DISCLOSURE STATEMENT

No potential conflict of interest was reported by the author(s).

Additional information

Notes on contributors

C. P. Koushik

C P Koushik received his under graduate degree in information technology from Anna University, Chennai, India and his master's degree in mobile and pervasive computing from Anna University, Chennai, India, in the year 2013. Completed his Doctor of Philosophy in School of Electronics Engineering, VIT University, Chennai Campus, India in the year 2021. His research interests are in wireless communications and networking, including routing in opportunistic networks, and energy-efficient wireless networking. Email: [email protected]

P. Vetrivelan

P Vetrivelan completed Bachelor of Engineering from the University of Madras, Chennai, and both Master of Engineering in embedded systems technologies and Doctor of Philosophy in information and communication engineering from Anna University, Chennai. He is working as a professor in the School of Electronics Engineering & assistant controller of examinations (ACOE) at Vellore Institute of Technology, Chennai, India. He has over 18 years of teaching experience in CSE and ECE Departments in both private engineering colleges in Chennai and private engineering University in Chennai, respectively. His research interests include wireless networks, adhoc and sensor networks, VANETs, embedded systems, and the internet of things (IoT) with machine learning. Corresponding author. Email: [email protected]

Elizabeth Chang

Elizabeth Chang is professor in School of ICT, Griffith University, Gold Cast Campus, Australia. She was earlier with Logistics and Canberra Fellow at the UNSW Canberra at the Australian Defence Force Academy (ADFA). Chang leads the defence logistics research group at UNSW, focusing on the key issues in logistics, big data management, defence logistics and sustainment, predictive analytics, situation awareness, IoT and cyberphysical systems, trust, security, risk and privacy. She has delivered 50+ keynote/plenary speeches at major IEEE conferences and in the area of semantics, business intelligence, big data management, data quality and the like. Her academic achievement includes 27 Competitive Research Grants including 12 Australian Research Council (ARC) grants worth over $21 million. She has supervised/co-supervised 54 PhD theses to completion, 30 Master's theses and 25 post-docs. She has published seven books, over 600 international journal papers and conference papers with an H-Index of 58 (Google Scholar) and over 17,000 citations. She is an IEEE Fellow and has been chair/co-chair for IEEE IES Technical Committee on Industrial Informatics since 2010. She has been chair of the IFIP International Working Group 2.1/12.4 since 2012. She is also an associate editor for IEEE Transactions on Industrial Electronics (since 2007); Co-editor in Chief for International Journal on Engineering Intelligent Systems. She is a member of Council of Supply Chain Management Professionals, honorary member of the Australian Logistics and Supply Chain Society. She was honored to be the general chair and technical chair for over 20 international and IEEE conferences. Email: [email protected]