A Hybrid Genetic Algorithm for Process Scheduling in Distributed Operating Systems Considering Load Balancing.
Abolfazl Toroghi Haghighat, Mohammad Nikravan
Abstract
Abolfazl Toroghi Haghighat, Mohammad Nikravan
Abstract
This paper presents and evaluates a new method for process scheduling in distributed systems. Scheduling in distributed operating systems has a significant role in overall system performance and throughput. An efficient scheduling is vital for system performance. The scheduling in distributed systems is known as an NPcomplete problem even in the best conditions, and methods based on heuristic search have been proposed to obtain optimal and suboptimal solutions. In this paper, using the power of genetic algorithms we solve this problem considering load balancing efficiently. We evaluate the performance and efficiency of the proposed algorithm using simulation results.
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This paper presents and evaluates a new method for process scheduling in distributed systems. Scheduling in distributed operating systems has a significant role in overall system performance and throughput. An efficient scheduling is vital for system performance. The scheduling in distributed systems is known as an NPcomplete problem even in the best conditions, and methods based on heuristic search have been proposed to obtain optimal and suboptimal solutions. In this paper, using the power of genetic algorithms we solve this problem considering load balancing efficiently. We evaluate the performance and efficiency of the proposed algorithm using simulation results.
Key concepts: Computer science, Fair-share scheduling, Distributed computing, Round-robin scheduling, Rate-monotonic scheduling, Scheduling (production processes), Dynamic priority scheduling, Load balancing (electrical power)