A Hybrid Gravitational Emulation Local Search-Based Algorithm for Task Scheduling in Cloud Computing

The flexibility of cloud computing to provide a dynamic and adaptable infrastructure in the context information technology service quality has made it one most challenging issues computer industry. Task scheduling is major challenge computing. Scheduling tasks so that they may be processed by effective network resources been identified as critical for maximizing computing’s performance. Due complexity issue size search space, random techniques are often used find solution. Several algorithms have offered possible solutions this issue. In study, we employ combination genetic algorithm (GA) gravitational emulation local (GELS) overcome task GA particle swarm optimization (PSO) compared suggested demonstrate its efficacy. outperforms PSO, shown experiments.