Optimized clustering using soft computing approaches in wireless sensor networks: research dimensions and contributions

Abstract

Presently, Wireless Sensor Network (WSN) is considered as the most prominent technologies employed in commercial as well as in industrial sector. The WSN comprises of battery-operated nodes that are used to monitor the surroundings in order to keep record of the physical phenomenon like temperature, pressure, position, vibration, humidity, sound etc. These nodes can be utilized in several real-time application domains to perform different tasks like target tracking, home surveillance, pollution monitoring, structural monitoring etc. Depending on the type of nodes deployment and the application areas, WSNs can be exploited underground, underwater, terrestrial, wearable or environment embedded. Firstly, this paper categorizes research dimensions in wireless sensor networks primary and secondary research domains and the research contributions in those fields. Secondly, it discusses different soft computing-based clustering schemes from past two decades to deal with energy conservation issue in sensor networks. This paper provides a clear insight to the beginners of this field by covering literature review from 2008 to 2020.