Efficient Task Scheduling in Cloud Systems with Adaptive Discrete Chimp Algorithm

Successful task scheduling is one of the priority actions to increase energy efficiency, commercial earnings, and customer satisfaction in cloud computing. On other hand, since processes are NP-hard problems, it difficult talk about an absolute solution, especially scenarios with large numbers. For this reason, metaheuristic algorithms frequently used solving these problems. This study focuses on metaheuristic-based solution optimization makespan, which important problems The adapted Chimp Optimization Algorithm, enhanced exploration exploitation phases, proposed for first time solve solutions obtained from algorithm, can use different mathematical functions, discussed comparatively. also tested CloudSim simulator they prove their performance environment.