Design of Task Scheduling and Fault Tolerance Mechanism Based on GWO Algorithm for Attaining Better QoS in Cloud System

Cloud computing has emerged as an effective system for rendering services to the user with the help of available resources. This creates a massive workload on the resources, which finally leads to a loss of network performance. To overcome the problem of workload, a process of task scheduling is utilized. Various research scholars have designed numerous scheduling algorithms in recent years. But for attaining efficient task execution with less failure rate and increased throughput, the proposed system is designed. In this proposed work, task execution is achieved with the help of grey wolf optimization (GWO). Along with task scheduling, fault detection is done simultaneously to reschedule the failed tasks. The proposed framework is executed on JAVA to carry out an experimental analysis. Further, the effective functioning of the proposed architecture is estimated using some of the performance matrices such as makespan, execution time, communication delay, computational delay, failure and utilization rates are evaluated. And to demonstrate the superiority of the proposed method in contrast with the conventional technique, a comparative analysis is carried out.