Hybrid Optimization Model for Secure Task Scheduling in Cloud: Combining Seagull and Black Widow Optimization

被引:7
作者
Verma, Garima [1 ]
机构
[1] DIT Univ, Sch Comp, Dehra Dun, India
关键词
Cloud; execution time; makespan; optimization; task scheduling; GENETIC ALGORITHM; ALLOCATION; FRAMEWORK;
D O I
10.1080/01969722.2022.2157609
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Task scheduling is the act of allocating tasks in a certain way to make the best use of the resources at hand. Users of the service must make their demands online since cloud computing is the method used to offer services through the internet. In this paper, a new hybrid optimization model is introduced for secure task scheduling in cloud which includes six fold objective functions such as makespan, execution time, Quality of Service (QoS), utilization cost and security. In security constraint, trust evaluation and risk probability was determined. Black Widow Combined Seagull Optimization (BWCSO) algorithm was proposed for obtaining the best optimization result by combining Black Widow Optimization (BWO) and Seagull Optimization Algorithm (SOA). Cycle crossover (CX) was introduced to produce an offspring from its parents in which each slot is filled by an element from a different parent. Finally, the suggested algorithm's performance was assessed, and the best outcome was found with respect to makespan.
引用
收藏
页码:2489 / 2511
页数:23
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