Multi-objective Task Scheduling Using Chaotic Quantum-Behaved Chicken Swarm Optimization (CQCSO) in Cloud Computing Environment

Abstract

AbstractTask scheduling is a challenging process with the increasing number of requests from the clients in a cloud system. Achieving efficient task scheduling with multiple objectives is much required in this modern era. A novel Chaotic Quantum-behaved Chicken Swarm Optimization (CQCSO) based task scheduling approach is presented in this paper. CQCSO is developed by applying chaotic theory and quantum theory to the standard Chicken Swarm Optimization to overcome its problem of premature convergence and local optima. CQCSO algorithm models the task scheduling as an optimization problem and solves it by formulating a multi-objective fitness function using task completion time, response time and throughput to ensure maximum Quality-of-service (QoS) satisfaction and minimum SLA violations. CQCSO identifies the task order and optimally schedules them to the suitable virtual machines with better performance. Experiments were conducted in CloudSim to evaluate the CQCSO approach and it provided efficient task scheduling than the prior existing algorithms. KeywordsCloud computingTask schedulingChaotic Quantum-Behaved chicken swarm optimizationQuality-of-serviceMulti-objective problem