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Published in: Wireless Personal Communications 4/2020

22-01-2020

Energy Efficient Dynamic Routing Mechanism (EEDRM) with Obstacles in WSN

Authors: Sharmila Selvaraj, Saranya Vasanthamani

Published in: Wireless Personal Communications | Issue 4/2020

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Abstract

In Wireless Sensor Networks, the in-built energy and processing capacity of sensors should be reliably used to ensure effective use of resources. The major pitfalls in WSN include network lifetime management, energy management and Obstacle avoidance. The paramount aim of proposed EEDRM protocol is to deliver better network efficiency thus uses the concept called clustering of sensor nodes. Cluster Heads are chosen based on energy, distance between cluster head (CH) and sink. Mobility enables high resource usage, hence in proposed work Cluster Heads are made mobile and routes in computed path. Obstacles in sensing environment is an important thing to be considered. EEDRM is designed in a way that it resists obstacles using travelling salesman problem, Hamiltonian Circuit algorithms and with the help of binary grid pattern in sensing environment. Data latency is reduced as CH is available all the time for receiving data from CM inside Cluster and all CH are independent to each other so data collected by CH will be transferred dynamically to the sink. Based on Obstacle avoidance model and node states an FSM is constructed using hidden Markov model. The increased network lifetime and throughput of EEDRM is analysed and compared with M-GEAR protocol. Analysis comes out with the result that EEDRM is 1.82 times better than M-GEAR and 3.92 times better than LEACH ME in terms of throughput and in terms of network lifetime EEDRM outperforms M-GEAR by 1.2 times and LEACH ME by 1.54 times.

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Metadata
Title
Energy Efficient Dynamic Routing Mechanism (EEDRM) with Obstacles in WSN
Authors
Sharmila Selvaraj
Saranya Vasanthamani
Publication date
22-01-2020
Publisher
Springer US
Published in
Wireless Personal Communications / Issue 4/2020
Print ISSN: 0929-6212
Electronic ISSN: 1572-834X
DOI
https://doi.org/10.1007/s11277-020-07174-9

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