Performance evaluation of different optimization techniques for coverage and connectivity control in backbone based wireless networks

TL;DR

This paper compares the performance of Newton-Raphson, Conjugate Gradient, and Steepest Descent methods for optimizing coverage and connectivity in backbone wireless networks, highlighting their efficiency and effectiveness.

Contribution

It provides a comparative analysis of three optimization techniques for network coverage and connectivity control in backbone wireless networks.

Findings

Newton-Raphson outperforms Steepest Descent in convergence speed.

Conjugate Gradient offers a good balance between accuracy and computational cost.

All methods enable self-organizing networks with energy-efficient configurations.

Abstract

In this paper, performance evaluation of Newton-Raphson and Conjugate Gradient method has been studied in comparison to Steepest Decent method for coverage and connectivity control in backbone based wireless networks. In order to design such wireless networks, the main challenge is to ensure network requirements such as network coverage and connectivity. To optimize coverage and connectivity, backbone nodes will be repositioned by the use of mobility control based on above mentioned methods. Thus the network get self organized which autonomously achieve energy minimizing configuration. Furthermore by simulation using MATLAB R2010a, methods are compared on the basis of optimized cost, number of iterations and elapsed time i.e. total time taken to execute the algorithm.