SELECTION USING ENHANCED NORMAL FORM GAME THEORY BASED OPTIMIZATION APPROACH IN WSN

S. Ponlatha; P. Sowmiyaa; D. Chitra

doi:10.29121/shodhkosh.v4.i2.2023.2305

Authors

Dr. S. Ponlatha Ph.D., Associate Professor., Department of Electronics and Communication Engineering in Mahendra Engineering college at Salem-Tiruchengode Highway, Mahendhirapuri, Mallasamudram, Namakkal(Dt)- 637503
P. Sowmiyaa B.E., M.E- Communication Systems (Student of Mahendra Engineering College)
Dr. D. Chitra Ph.D., Professor, Department of Electronics and Communication Engineering in Mahendra Engineering college at salem- Tiruchengode Highway, Mahendhirapuri, Mallasamudram, Namakkal(Dt)-637503

DOI:

https://doi.org/10.29121/shodhkosh.v4.i2.2023.2305

Keywords:

Heterogeneous Network, Optimization, Handover, Long Term Evolution (LTE), TOPSIS, Weight

Abstract [English]

Heterogeneous network is a network connecting mobile station (MS) with different kinds of wireless network. It will provide an efficient network connection for mobile users. When considering various wireless access technologies, it's difficult to search out reliable criteria to pick out the most effective offered wireless heterogeneous network. . Game theory techniques have been receiving growing attention in recent years as they can be adopted in order to model and understand competitive and cooperative scenarios between rational decision makers.In this paper, our aim is to develop an economical wireless network choice algorithm which is optimized using enhanced Normal Form Optimization Algorithm which follows game theory based procedure . This algorithm is proposed for optimizing the heterogeneous wireless environment comprising universal mobile telecommunication system (UMTS) and long term evaluation (LTE). Further, within optimization algorithm resource allocation is considered as an objective function. The incorporated optimization algorithm is involved in the optimal computation process for reducing channel complexity through optimal solution estimation. The computation complexity of proposed Normal Form Optimization Algorithm with TOPSIS method (NFOA-TOPSIS) measured in terms of running time and network utilization is measured in terms of the Packet Delivery Rate (PDR), throughput, simulation time, end-to-end delay and Power consumption. The simulation results expressed that the proposed NFOA provides reduced running time and increases PDR rather than conventional MADM (i.e., Hybrid Fuzzy Analytic Hierarchy Process (FAHP)& Technique for Order Preference by Similarity to an Ideal Solution -Hybrid FHAP-TOPSIS) method. The reduce in running time implies reduced complexity of proposed scheme. Also, the increase in PDR and throughput leads to reduced end-to-end delay and power consumption resulted in efficient utilization of available channels in heterogeneous networks.

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