Hybrid Optimization Model for Secure Task Scheduling in Cloud: Combining Seagull and Black Widow Optimization
Garima Verma
Abstract
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.