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A joint hybrid corona based opportunistic routing design with quasi mobile sink for IoT based wireless sensor network - 2021

A joint hybrid corona based opportunistic routing design with quasi mobile sink for IoT based wireless sensor network

Research Area:  Wireless Sensor Networks

Abstract:

The resource constrained wireless sensor embedded devices are deployed in the edge of the Internet of Things (IoT) system for smart monitoring and control of large scale Wireless Sensor Network (WSN) applications. A joint hybrid corona based Opportunistic Routing (OR) with path-constrained Quasi-Mobile Sink (QMS) is designed to address the challenges for (i) providing long term sustainable operation and scalability of WSN (ii) also counteract the hot-spot problem near the sink. This hybrid routing design adopted opportunistic mode of forwarding as it is first and last resort to increase transmission reliability, despite the time varying lossy radio links. The eligible relay-set based on the corona level it resides with respect to sink, collaborates for packet forwarding in a fully distributed online manner during the opportunistic mode. The priority order of relay(s) are determined on the fly based on multi-metrics fuzzy decision logic for timer based coordination and adopts a cross layered differentiated back off strategy for distributed priority based contention. The routing design switches to unicast mode of forwarding via the most trusted relay(s) for subsequent transmissions to increase the energy efficiency under stable link conditions. Simulation results shows that hybrid OR design achieves high end to end packet delivery ratio and minimizes the average energy consumed per node in comparison with existing routing protocol designs. The joint routing design with QMS is found to scale well and prevents the unbalanced energy consumption by minimizing the maximum energy dissipation and normalized energy consumption per packet compared to the Static Sink (SS) and Uncontrolled Mobility Model based Sink (UMM-S).

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Author(s) Name:  Jayavignesh Thyagarajan & Suganthi Kulanthaivelu

Journal name:  Journal of Ambient Intelligence and Humanized Computing

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Publisher name:  Springer

DOI:  10.1007/s12652-020-02116-6

Volume Information:  volume 12, pages 991–1009 (2021)