Task Scheduling Optimization in Cloud Computing by Jaya Algorithm
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TL;DR: In this paper , the authors proposed an efficient task scheduling algorithm based on the Jaya algorithm for the cloud computing environment, which produced the optimal solution in makespan, speedup, efficiency, and throughput.
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Abstract: Cloud computing provides resources to its consumers as a service. The cloud computing paradigm offers dynamic services by providing virtualized resources via the internet for enabling applications, and these services are provided by large-scale data centers known as clouds. Cloud computing is entirely reliant on the internet to provide its services to consumers. Cloud computing offers several advantages, including the fact that users only pay for what they use weekly, monthly, or yearly, that anybody with an internet connection may use the cloud, and that there is no need to purchase resources, hardware, or software on their own. This paper proposes an efficient task scheduling algorithm based on the Jaya algorithm for the cloud computing environment. We evaluate the performance of our method by applying it to three instances. The recommended technique produced the optimal solution in makespan, speedup, efficiency, and throughput, according to the findings.
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Citations
The Synchronous Dislocation Scheduling Algorithm: Cloud-Based Performance Improvement
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- 29 Dec 2023
References
Performance-effective and low-complexity task scheduling for heterogeneous computing
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A hybrid harmony search algorithm for the blocking permutation flow shop scheduling problem
TL;DR: A hybrid modified global-best harmony search algorithm for solving the blocking permutation flow shop scheduling problem with the makespan criterion with the largest position value (LPV) rule proposed to convert continuous harmony vectors into job permutations.
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A hybrid particle swarm optimization and hill climbing algorithm for task scheduling in the cloud environments
TL;DR: To optimize the task scheduling makespan, a hybrid particle swarm optimization and hill climbing algorithm is proposed and the experimental results showed that the proposed algorithm performs effectively in terms of the makespan compared to the current well-known heuristic and particle Swarm optimization algorithms.
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An Evolutionary Computing-Based Efficient Hybrid Task Scheduling Approach for Heterogeneous Computing Environment
TL;DR: In this article, a hybrid heuristic and genetic-based task scheduling algorithm for Heterogeneous Computing (HHG) is proposed to minimize the execution time of an application graph.
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