Increasing the Network life Time by Simulated Annealing Algorithm in WSN with Point Coverage

TL;DR

This paper proposes a simulated annealing algorithm to optimize sensor selection in wireless sensor networks, aiming to extend network lifetime by balancing energy consumption and considering remaining energy in point coverage scenarios.

Contribution

It introduces a novel simulated annealing-based method for sensor selection that effectively prolongs network lifetime in WSNs with point coverage.

Findings

Increases network lifetime through optimized sensor selection.

Balances energy consumption among sensors.

Simulation confirms improved energy efficiency.

Abstract

Since we are not able to replace the battery in a wireless sensor networks (WSNs), the issues of energy and lifetime are the most important parameters. In asymmetrical networks, different sensors with various abilities are used. Super nodes, with higher power and wider range of communication in comparison with common sensors, are used to cause connectivity and transmit data to base stations in these networks. It is crucial to select the parameters of fit function and monitoring sensors optimally in a point covering network. In this paper, we utilized an algorithm to select monitoring sensors. The selection is done by using a novel algorithm that used by simulated annealing. This selection takes remained energy into consideration. This method increases lifetime, decreases and balances energy consumption as confirmed by simulation results.