Simulation Analysis and Comparative Study of MOSGT with Other Techniques

Abstract

This paper presents a comparative study of the Multi-Objective Symmetric Game Theory (MOSGT) for task offloading in cloud robots with existing techniques such as Genetic Algorithm 4 Collaborative Computation Offloading (GA4CCO) and Approximation Collaborative Computation Offloading (ACCO). The study employs a simulation analysis to evaluate the performance of the proposed MOSGT model in a cloud robotics context. The results of the simulation study reveal that the MOSGT model reduces system cost by approximately 35% compared to GA4CCO and by 20% compared to ACCO. Furthermore, the MOSGT model exhibits a reduced rate of 30% less than GA4CCO and 25% minimal than ACCO in terms of iteration. These findings underscore the potential of MOSGT as a promising solution for efficient task offloading in cloud robots, offering significant improvements in computational complexity and service quality in edge computing.