Simulated Annealing for Optimal Placement of Wireless Sensor Network Nodes
Rahul Priyadarshi, Bharat Gupta, Sanchita Purohit Ghosh · 2024
Optimal placement of nodes is essential for achieving efficient network coverage, connectivity, and energy consumption in Wireless Sensor Networks (WSNs). This paper investigates the utilization of Simulated Annealing (SA), a probabilistic optimization technique inspired by the annealing process in metallurgy, for solving the problem of node placement in WSNs. We have developed an approach utilizing simulated annealing that systematically improves the placement of nodes by effectively exploring and exploiting the solution space. We do extensive simulations to assess the effectiveness of the SA-based strategy in comparison to traditional methods. The results suggest that the adoption of SA significantly enhances the scope and excellence of network coverage and connectivity, while concurrently reducing energy consumption. The results highlight the capacity of Simulated Annealing as a dependable and efficient method for enhancing the placement of WSN nodes. This has the potential to result in the creation of sensor networks that are more resilient and consume less energy.