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Corresponding Author

Maha Zeedan

Subject Area

Computer and Control Systems Engineering

Article Type

Original Study

Abstract

This paper proposes enhanced load balancer based artificial bee colony and β-Hill climbing for improving the performance metrics such as response time, processing cost, and utilization to avoid overloaded or under loaded situations of virtual machines. In this study, the suggested load balancer is called enhanced load balancing based on hybrid artificial bee colony with enhanced β-Hill climbing (ELBABCEβHC) to improve the response time, processing cost and the resource utilization. Our proposed approach starts by ranking the task then the greedy randomized adaptive search procedure (GRASP) is used in initializing populations. Further, the binary artificial bee colony (BABC) enhanced with the modified β-Hill climbing with the sinusoidal map strategy is applied to schedule tasks considering load balancing in cloud. The proposed approach is implemented in CloudAnalyst. The experimental results show that for different user groups all over the world. the performance of ELBABCEβHC algorithm outperforms round robin (RR), throttled load balancer (TLB), and active monitoring load balancing (AMLB) algorithms considering response time, processing cost and utilization.

Keywords

Cloud computing, Load balancing, Scheduling, algorithms, and Artificial Bee Colony

Creative Commons License

Creative Commons Attribution 4.0 License
This work is licensed under a Creative Commons Attribution 4.0 License.

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