An Evolutionary Study of Multi-Objective Workflow Scheduling in Cloud Computing

Cloud computing become more popular in every field of life nowadays. This happened only due to its amazing services that provide to clients in the form of everything-as-aservice(XaaS). Where at one side cloud computing is gaining popularity and another side its faces some issues i.e. security issue, total cost issue, energy consumption issue, performance issue, QoS issue, etc. In above all challenges the quality of services is the most noticeable challenge and affects the cloud computing services. Quality of services can be improved by considering the several factors, scheduling of workload for suitable cloud computing resources one of them. If the cloud computing resources are scheduled accurately, it affects the response time of services, total cost of cloud resources, reduce the energy consumption, reduce the CO2 emission and enhance the performance of whole cloud system. In this paper, we characterize a comparative review of multiobjective workflow scheduling algorithms that are listed below.