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Optimized mobility management for RPL/6LoWPAN based IoT network architecture using the firefly algorithm
Affiliation:1. Research Scholar, Dept. of Computer Science and Engineering, Adhiparasakthi Engineering College, Melmaruvathur, India;2. Professor & Vice Principal, Dept. of Electronics and Communication Engineering, Adhiparasakthi Engineering College, Melmaruvathur, India;1. Research Scholar, Dept. of Computer Science and Engineering, Adhiparasakthi Engineering College, Melmaruvathur, India;2. Professor & Vice Principal, Dept. of Electronics and Communication Engineering, Adhiparasakthi Engineering College, Melmaruvathur, India;1. Department of Computer Engineering, Sharif University of Technology, Tehran, 11155-11365, Iran;2. School of Computer Science, Institute for Research in Fundamental Sciences, Tehran, 19395-5531, Iran;1. Research Centre on Scientific and Technical Information, 03, Rue des Freres Aissou, Ben Aknoun, Algiers, Algeria;2. Departement Informatique, Faculte des Sciences Exactes, Universite de Bejaia, Bejaia 06000, Algeria;3. Edinburgh Napier University, School of Computing, 10 Colinton Road, Edinburgh, EH10 5DT, UK
Abstract:RPL (Routing Protocol for low-power and Lossy Networks) is a new attractive model that secures the networks from different routing risks. The dynamic environment and limited resources motivated the research towards identifying a stable, reliable, energy efficient, and scalable routing design. IPv6 over low-power Wireless Personal Area Network (6LoWPAN) is a standard RPL IPv6 routing protocol that provides Low power and Lossy Networks (LLNs) interoperability. In this research work, an energy efficient and optimization-based mobility management framework in RPL routing protocol was proposed (mRPL-based firefly optimization algorithm) to achieve a reliable and stable protocol. From the results, it can be inferred that the proposed system (mRPL+firefly optimizer) showed better performance with regard to the Packet_Delivery_Ratio (PDR), number of hops, End_To_End delay and power consumption when compared to existing systems: RPL, mRPL, mRPL+PSO, and mRPL+ACO. The experimental outcome showed that the proposed system improved the PDR on an average of 2.31% in comparison with existing systems.
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