Abstract
Cloud-based job scheduling is used to achieve high throughput. The problem of load balancing hampers the performance of the cloud. To end this, the bees life algorithm is used to achieve optimization in job scheduling. This paper proposes unique dynamic scheduling using the bees algorithm with the shortest job first approach to achieve a high degree of load balancing. The effectiveness of cloud computing depends greatly upon the performance of the cloud scheduler. The scheduling algorithm used achieves high performance, since waiting time for jobs is reduced. The overall algorithm is divided into phases. The first phase is the initialized section in which fog and execution nodes are defined. In the second phase, job fetching and uploading are accomplished. In the third phase, jobs are sorted according to the shortest burst time. In the last phase, bees are deployed to locate the best possible processor for job execution. The result of the dynamic bees algorithm shows effective load balancing as compared to the static bees algorithm. Result in terms of execution time, waiting time, execution speed, and memory allocation shows improvement by 2–3%.
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Singh, H., Marwaha, C. (2021). Optimization of Job Scheduling with Dynamic Bees Approach. In: Karuppusamy, P., Perikos, I., Shi, F., Nguyen, T.N. (eds) Sustainable Communication Networks and Application. Lecture Notes on Data Engineering and Communications Technologies, vol 55. Springer, Singapore. https://doi.org/10.1007/978-981-15-8677-4_12
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