Genetic Algorithm Framework for Bi-objective Task Scheduling in Cloud Computing Systems

Cloud computing gives an excellent opportunity for business enterprises as well as researchers to use the computing power, over Internet, without actually owning the infrastructure, there by reducing establishment and management cost. Task scheduling in cloud systems is challenging due to the conflicting objectives of end users and the cloud service providers. Running time and cost are two key factors that determine the optimal service from the cloud. In this paper, we focus on two objectives, makespan and cost, to be optimized simultaneously using genetic algorithm framework. Finding an optimal schedule, considering both of these conflicting objectives, is a search problem under NP-hard category. We have considered the scheduling of independent tasks and the proposed frame work can be used in public or hybrid cloud.