K-medoid based Efficient and Sustainable Utilizations of Sensor Networks with Minimal Traffic

Abstract

This research study introduced the Efficient and Sustainable Utilizations of Sensor Networks with Minimal Traffic during the wireless network transmission. The components are interlinked and function in a collaborative manner to transmit accumulated data to a central sink or base station that receives it. Efficient and sustainable utilization of sensor networks necessitates minimal traffic within the networked sensors (WSNs). These networks comprise multiple sensor nodes that are interconnected, and their optimal performance is achieved through the avoidance of congestion, low energy consumption, elimination of duplicate information transmission, and minimal data transfers to the sink. Efficient attainment of these objectives necessitates the use of data aggregation. The principal objective of data aggregation is to effectively collect and merge data, while simultaneously eliminating superfluous data in order to improve the longevity of the network.

Objectives: The objective is to enhance data collection in wireless sensor networks, to identify the Efficient and Sustainable Utilizations of Sensor Networks with Minimal Traffic, thereby demonstrating an improved cluster head selection rate and a better minimum distance rate between two nearby nodes through the proposed scheme.

Methods: This study's review centered on various information aggregation methods, such as flat networks, hierarchical systems, and structure-free systems, and their respective variations. The current research centres on the initiation of work pertaining to energy-efficient data collection and the administration of large databases through the utilisation of distinct models such as K-medoid, k-means, and fuzzy-based clustering mechanisms for validation.

Results: Overall, the implementation of the proposed scheme yields a performance improvement of more than 13 to 17% when compared to the results obtained from the current system.

 Conclusions:   The researcher proposed an energy-efficient coverage control algorithm for WSNs based on Particle Swarm Optimization (PSO).In order to achieve a balance among coverage rate and cost of energy, the detection radius of every sensor node is adjusted with the objective of attaining this goal. So, for that, we design a proposed system that uses data aggregation using PSO with a k-medoid-based method for design and implements data transmission on low power and also energy efficiency