Multiple Processor Scheduling with Optimum Execution Time and Processor Utilization Based on the SOSA

Abstract

The multiple processor scheduling problem characterizes that different processor comprises of an arrangement of jobs or tasks designate proficient utilizing a limited number of processors. Herein development a multi-objective algorithm utilizing Symbiotic Organisms Search algorithm (SOSA) for scheduling an arrangement of reliant on tasks on obtainable resources in a multiple processor environment which minimizes the execution time and maximize the processor utilization. SOSA is a nature-inspired meta-heuristic algorithm utilized to compare with other meta-heuristic algorithms such as Water cycle algorithm (WCA), Genetic algorithm based Bacteria foraging optimization (GBF), Bacteria Foraging Optimization (BFO) and Genetic Algorithm (GA). SOSA reproduces the advantageous association methodologies received by life forms to survive and engender in the biological-community (ecosystem). Based on experimental results, we find the execution time as well as processor utilization using SOSA technique and then compare with the other mentioned algorithms. Acquired outcomes affirm the incredible execution of the SOSA in solving the multiple processor scheduling problems.