Abstract
In today’s research of multidisciplinary environment, heterogeneous devices are connected to meet the performance by solving the popular real-life applications like IoT for developing a cyber-physical system, smart healthcare and agriculture, etc. Such a heterogeneous system is risky to maintain its regularities in terms of scheduling the resources for better optimal throughputs. In this paper, we target to develop an optimal resource scheduling system in the cloud environment. More specifically, the improved load balancing algorithms are developed which give optimal allocation of the resources requested by the virtual machine. In the proposed algorithmic approach, the major efforts are to focus on developing an optimal load balancing system for allocating various tasks to virtual machines. The popular scheduling algorithm in a multitasking environment, the Round-Robin algorithm, allocates the task to VM on FCFS basis. In this paper, generalized priority-based modified shortest job first (MSJF), a premier load balancing algorithm is joint which resulted in a scheme that is effectively suitable for resource optimization and reduces the makespan at a large scale. We further presented the important objective of the load balancing technique via showing the difference between makespan and resources allocation by implementing RR, FCFS and MSJF. To optimize the allocation of available resources among the task with different requests, the proposed system satisfactorily reduces makespan and deactivates idea resources.
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Gupta, N.K., Walia, A., Sharma, A. (2022). GP-MSJF: An Improved Load Balancing Generalized Priority-Based Modified SJF Scheduling in Cloud Computing. In: Goar, V., Kuri, M., Kumar, R., Senjyu, T. (eds) Advances in Information Communication Technology and Computing. Lecture Notes in Networks and Systems, vol 392. Springer, Singapore. https://doi.org/10.1007/978-981-19-0619-0_51
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DOI: https://doi.org/10.1007/978-981-19-0619-0_51
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