New Improved Multi-Objective Gorilla Troops Algorithm for Dependent Tasks Offloading problem in Multi-Access Edge Computing

Abstract Computational offloading allows lightweight battery-operated devices such as IoT gadgets and mobile equipment to send computation tasks nearby edge servers be completed, which is a challenging problem in the multi-access computing (MEC) environment. Numerous conflicting objectives exist this problem; for example, execution time, energy consumption, cost should all optimized simultaneously. Furthermore, an application that consists of dependent another important issue cannot neglected while addressing problem. Recent methods are single objective, computationally expensive, or ignore task dependency. As result, we propose improved Gorilla Troops Algorithm (IGTA) offload MEC environments with three objectives: 1-Minimizing latency application, 2-energy consumption light devices, 3-the used resources. it supposed each supports many charge levels provide more flexibility system. Additionally, have extended operation standard (GTO) by adopting customized crossover improve its search strategy. A Max-To-Min (MTM) load-balancing strategy was also implemented IGTA operation. Relative GTO, has reduced 33%, 93%, usage 34.5%. We compared other Optimizers problem, results showed superiority IGTA.