Certain investigations on load balanced meta heuristic scheduling algorithms in cloud computing

Abstract

The Cloud Computing technique is mostly used when the newlinedemand of user is unpredictable or the user/business requires resources for newlinecomputing, because the user does not want to invest in a computing newlineinfrastructure. The virtualization technique is mainly used for the efficient newlineuse of the cloud resources. The cloud computing approach concentrates on newlineresources in a large data center which is within a single administrative newlinedomain. Despite the facts that cloud infrastructure, distribute and newlinebalance the load automatically, there is a complexity in scheduling. Since, newlinescheduling is a critical component of the cloud resource management as it has newlinevery large number of shared resources. The IaaS service model plays a newlinesignificant role in allocating resources on-demand, efficient utilization of newlineresources and proper load balancing. Load Balancing and Task Scheduling newlineare the core and challenging issues in the cloud environment. In order to maintain all the resources available and to distribute the load equally, efficient load balancing algorithms are required for the newlinecloud. The complexity of the task scheduling algorithms belongs to NP-Hard newlineproblem which requires large search space with a number of solutions and for newlinefinding an optimal solution it takes longer time. An optimized load balanced task scheduling approach with newlinemulti-objective fitness function is proposed in order to balance the load of the newlineentire cloud, and to bring down the makespan, to improve resource utilization newlineand to reduce network load in the cloud. newline newline