JOURNAL ARTICLE

An Optimal Cluster-Head Selection algorithm for Wireless Sensor Networks

Khushboo JainAnoop Kumar Bhola

Year: 2020 Journal:   WSEAS TRANSACTIONS ON COMMUNICATIONS Vol: 19 Pages: 1-8   Publisher: World Scientific and Engineering Academy and Society

Abstract

The energy utilization is one of the most common challenges in Wireless Sensor Network (WSN), as frequent communication between the sensor nodes (SNs) results in huge energy drain. Moreover, optimization and load balancing within the WSN are the significant concern to grant intellect for the extensive period of network lifetime. As a matter of fact, many WSNs are deployed and operating outdoors is exposed to varying environmental conditions, which may further set grounds for severe performance degradation of such networks. Therefore, it is necessary to take into consideration the factors like radio signal strength in order to reduce the impact and to adapt to varying environmental conditions. Since clustering is a topological control technique to reduce the activity of SNs transceivers, it extensively increases overall system scalability and energy efficiency. It selects CH to manage the entire network to achieve longevity in WSN. In this paper, we present an optimal CH selection (OCHS) algorithm which is also based on environmental conditions to achieve energy efficiency and enhanced network lifetime. The originality of this work is that we have taken into consideration the received signal strength index (RSSI) of SNs from the base-station (BS). The OCHS algorithm mainly focuses on maximizing the network lifetime based on RSSI values and residual energy levels of SNs. TheOCHS algorithm is simulated on Cooja Simulator and its performance is compared with existing LEACH and HEED protocols. Simulation analysis and results proved that our OCHS algorithm can effectively enhance the network lifetime by two times and thus it is an energy-efficient way to choose a CH.

Keywords:
Wireless sensor network Computer science Scalability Base station Cluster analysis Selection algorithm Efficient energy use Energy (signal processing) Energy consumption Transceiver Computer network Selection (genetic algorithm) Wireless Real-time computing Telecommunications Engineering Artificial intelligence Electrical engineering

Metrics

8
Cited By
1.19
FWCI (Field Weighted Citation Impact)
17
Refs
0.80
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Energy Efficient Wireless Sensor Networks
Physical Sciences →  Computer Science →  Computer Networks and Communications
Energy Harvesting in Wireless Networks
Physical Sciences →  Engineering →  Electrical and Electronic Engineering
Advanced MIMO Systems Optimization
Physical Sciences →  Engineering →  Electrical and Electronic Engineering
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