Multiple Processor Scheduling with Optimum Execution Time and Processor Utilization Based on the SOSA
Sasmita Kumari Nayak1, Chandra Sekhar Panda2 

1Sasmita Kumari Nayak, Department of Computer Science and Engineering, Centurion University of Technology and Management, Bhubaneswar, Odisha, India.
2Chandra Sekhar Panda, Department of Computer Science and Application department, Sambalpur University, Odisha, India.

Manuscript received on 13 March 2019 | Revised Manuscript received on 18 March 2019 | Manuscript published on 30 July 2019 | PP: 5463-5471 | Volume-8 Issue-2, July 2019 | Retrieval Number: B3756078219/19©BEIESP | DOI: 10.35940/ijrte.B3756.078219
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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.
Index Terms: Meta-heuristic Algorithm, Multiple Processor Scheduling, Optimization Problem, Symbiotic Organisms Search (SOSA).

Scope of the Article: Simulation Optimization and Risk Management