BWFSO: Hybrid Black-widow and Fish swarm optimization Algorithm for resource allocation and task scheduling in cloud computing. (2022)

• Record Type: Journal Article
• Authors: Manikandan, N.; Divya, P.; Janani, S.
• Is Part Of: Materials today. Volume 62:Part 7(2022)
• Page Start: 4903
• Page End: 4908
• Publication Date: 2022
• Subjects: Optimization -- Makespan -- Cost -- Energy -- Resource utilization -- Metaheuristic; BWFSO Black-widow and Fish swarm optimization; Materials science -- Congresses -- Periodicals; 620.1
• DOI: 10.1016/j.matpr.2022.03.535
• Languages: English
• ISSNs: 2214-7853

Abstract

Abstract: Cloud computing has been booming technology in recent years. It is used to share resources over the internet. Though cloud has many advantages and is used worldwide. It also has some disadvantages and issues. The major problem in cloud computing is scheduling and resource allocation. Allocating resources and tasks is one of the highly critical challenges. There are no proper methods or techniques to improve task scheduling and resource allocation. Previous methods used Virtual machine (VM) instances for scheduling. The major drawback of using Virtual machine instances is that it takes a lot of startup time and consumes all the resources to perform the task. In this paper, we have proposed a solution with fuzzy C-means clustering hybrid algorithms of using Black widow optimization for task scheduling and fish swarm optimization for efficient resource allocation to reduce cost, energy, resource utilization.