Project Abstract

Wireless Sensor Mesh Networks heavily rely on the strategic placement of nodes, essential for efficient data transmission and network reliability. Unlike other network topologies, mesh networks route data through intermediate nodes to reach a base station. This paper focuses on designing an objective function that accurately assesses node efficiency based on Connectivity and Coverage metrics. We then apply optimization algorithms, specifically Simulated Annealing and Random Search, to find the optimal node configuration.Our study investigates two different placement strategies to achieve node placement optimization. Simulated Annealing and Random Search algorithms are employed, aiming to maximize network coverage by optimizing node positions based on the defined objective function. We compare the performance of these methods to gain insights into the most effective node placement strategy.Our findings reveal that a sequential approach to node placement, particularly with Simulated Annealing, shows promise with minor adjustments to the objective function. However, Random Search emerges as the top performer in optimizing node placement for enhanced network Connectivity and Coverage. This study aims to contribute to advancing the understanding of optimal node placement strategies in wireless sensor mesh networks.

Keywords: Optimisation, Mesh Network, Simulated Annealing

 Conference Details

Session: Poster Session A at Poster Stand 105

Location: Sir Stanley Clarke Auditorium at Tuesday 7th 13:30 – 17:00

Markers: Alma Rahat, Jen Pearson

Course: MSci Computer Science, 3rd Year

Future Plans: I’m continuing studies