Task Scheduling Using TVIW-PSO in Cloud Computing

被引:1
|
作者
Krishna, B. Siva Rama [1 ]
Krishna, T. Murali [1 ]
Sri, J. Bhavya [1 ]
Priya, B. Vishnu [1 ]
机构
[1] Lakireddy Bali Reddy Coll Engn, Comp Sci & Engn, Mylavaram 521230, India
关键词
Task Scheduling; Throughput; Makespan; Particle Swarm Optimization; Time Varying Inertia; Cloud computing; ALGORITHM;
D O I
10.1109/ACCAI61061.2024.10602168
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Cloud with increased resource usage is crucial to decrease expenses. Regarding cloud computing, the resource allocation and scheduling tasks playa Important role in the quest for cost-efficiency, maximizing resource utilization within cloud environments is key. This is where optimizing task scheduling comes in, and a promising approach emerges a multi-variant particle swarm optimization this explores PSO's adaptability to task scheduling, highlighting its ability to improve load balancing, reduce execution time, and improve resource allocation in cloud environments, further refining its effectiveness in cloud task scheduling. It's a promising avenue for achieving cost-effective and high-performance cloud operations, paving the way for a more efficient and scalable future.
引用
收藏
页数:7
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