Weight influence of logarithmic and exponential functions on the selection of wireless networks using multi-criteria decision-making methods

Abstract

This research aims to study the influence of logarithmic and exponential functions on the multi-criteria decision-making algorithm that changesthe linear to the nonlinear method. It is carried out to better understand themulti-criteria decision-making (TOPSIS) algorithm whereby these functionsmay influence the criteria weights during the selection of the best network. Theexperiment is applied under different network types to evaluate the most optimumnetwork that leads to better throughput, low latency, minimum BER, andlow price per MB. The algorithms are assessed in MATLAB simulation environments.In addition, the adoption of the Wi-Fi networks standard is determined byfactors such as bandwidth, signal to noise ratio and the channel modulation techniqueduring the decision-making process. The simulation results showed thatthe exponential function had produced approximately similar results to that oflinear TOPSIS algorithm because both keep the weights to demonstrate positivevalues. However, logarithmic TOPSIS produced different results and a worstcasescenario, as the weights have negative values which lead to a phase shift of180° during the decision process. Thus, linear TOPSIS was found to have the bestresults while logarithmic TOPSIS had the worst outcome.