Title

M-SPOT: A hybrid multiobjective evolutionary algorithm for node placement in wireless sensor networks

Document Type

Conference Proceeding

Publication Date

7-20-2018

Publication Title

Proceedings - 32nd IEEE International Conference on Advanced Information Networking and Applications Workshops, WAINA 2018

Volume

2018-January

First Page

264

Last Page

269

Keywords

Energy, Hybrid Algorithms, Multiobjective Evolutionary Algorithms, Multiobjective Optimization, Relay Node Placement, Wireless Sensor Networks

Abstract

© 2018 IEEE. We address the problem of the placement of static sensors and relays to monitor specific locations in an area assuming a single-tiered wireless sensor network model with limited communication and sensing constraints. We present a multiobjective optimization model with two conflicting objectives: total number of devices used in the placement and total energy dissipated by the placement. To optimize the model, we propose the Multiobjective Sensor Placement Optimizer (M-SPOT) algorithm, which is a hybrid evolutionary algorithm that combines the Non-Sorting Genetic Algorithm 2 (NSGA2) algorithm with local search heuristics. We evaluate the performance of M-SPOT by simulating the placement of sensors and relays. We found that the utilization of local search heuristics greatly contribute to find better placements when compared to the NSGA2 algorithm.

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