Paper Info
Title
Multi objective task scheduling based on hybrid metaheuristic algorithm for cloud environment
Abstract
Cloud computing is gaining a huge popularity for on-demand services on a pay-per-use basis. However, single data centre is restricted in offering the services, as it does not have unlimited resource capacity mostly in the peak demand time. Generally, the count of Virtual Machines (VM) is more in public cloud; still, the security is not ensured. In contrast, the VMs are limited in private cloud with high security. So, the consideration of security levels in task scheduling is remains to be more critical for secured processing. This works intends to afford the optimization strategies for optimal task scheduling with multi-objective constraints in cloud environment. Accordingly, the proposed optimal task allocation framework considers the objectives such as execution time, risk probability, and task priority. For this, a new hybrid optimization algorithm known as Clan Updated Seagull Optimization (CUSO) algorithm is introduced in this work, which is the conceptual blending of Elephant Herding Optimization (EHO) and Seagull Optimization Algorithm (SOA). Finally, the performance of proposed work is evaluated over other conventional models with respect to certain performance measures.
Year
DOI
Venue
2022
10.3233/MGS-220218
MULTIAGENT AND GRID SYSTEMS
Keywords
DocType
Volume
Cloud computing, virtual machine, task scheduling, optimization, execution time
Journal
18
Issue
ISSN
Citations 
2
1574-1702
0
PageRank 
References 
Authors
0.34
0
2
Name
Order
Citations
PageRank
P. Neelakantan100.34
N. Sudhakar Yadav200.34