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International Journal of Sensors, Wireless Communications and Control

Editor-in-Chief

ISSN (Print): 2210-3279
ISSN (Online): 2210-3287

Research Article

Optimization Based Sink Deployment Technique in WSN to Improve Network Performance

Author(s): Sonal Telang Chandel* and Sanjay Sharma

Volume 10, Issue 2, 2020

Page: [217 - 230] Pages: 14

DOI: 10.2174/2213275912666190410150204

Price: $65

Abstract

Background & Objective: Currently, WSN (Wireless Sensor Networks) provides a variety of services in industrial and commercial applications. WSN consists of nodes that are used to sense the environments like humidity, temperature, pressure, sound, etc. As the use of WSN grows there are some issues like coverage, fault tolerance, a deployment problem, localization, Quality of Service, etc. which needs to be resolved. Sink deployment is a very important problem because it is not the only impact on performance, but also influence on deployment cost. In traditional WSN, a single sink is deployed in the network, which aggregates all the data. Due to this, the whole network is suffering from some serious issues like delay, congestion, network failure that reduces network performance.

Methods: One solution is to deploy multiple sinks instead of a single sink. Deploying multiple sinks can improve network performance, but increases sink deployment cost. In this paper, an ISDOA (Improved Sink Deployment Optimization Algorithm) is proposed to find the optimum number of sinks and their optimum location in ROI. Simulation is carried out in Matlab simulator. The impact of sensors and sinks on various network performance parameters like throughput, network lifetime, packet delivery ratio, energy consumption and cost of the network is analyzed.

Results & Conclusion: It is shown by simulation results that the number of sinks varies inversely with energy consumption of the nodes; and it is linearly proportional to the network lifetime, throughput and packet delivery ratio. Furthermore, results show that the proposed approach outperforms random deployment with 25% higher throughput, 30% better network lifetime, 15% lesser energy consumption and 21% optimized cost of the network, respectively.

Keywords: Cost of the network, deployment problem, energy consumption, network lifetime, optimization technique, packet delivery ratio, throughput, wireless sensor network.

Graphical Abstract
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