Load Balancing Enhanced Technique for Static Task Scheduling in Cloud Computing Environments

Abstract

Cloud computing has become an actual opportunity to supercomputing framework for creating proportional applications that associate enormous computational resources. Though, the difficulty acquired in constructing such parallel cloud mindful applications is higher than the ordinary parallel computing framework. It reports concerns for instance resource finding, heterogeneity, fault tolerance, and Tasks scheduling. Load balanced task scheduling in cloud computing is a vital issue, it is one of the NP-Completeness Problem, So Considered the focus of attention researchers in the cloud computing scope. The conventional Min-min and Max-min are a simple algorithm that creates a schedule that reduces the Makespan, regardless of load balancer, resource utilization, and resource usage effectively. To over-awed such restrictions, in this paper, a new load balance scheduling algorithm (SSLB) is designed and applied. This study focuses on static batch scheduling with the number of accessible resources and Received Tasks. Initially, it uses the Min-min or Max-min allocation map. SSLB utilizes the equal running time of the standard Min-min or Max-min. SSLB algorithm depends on the normal execution time rather than complete time as a determination premise. Experimental outcomes demonstrate the accessibility of load balance in cloud computing framework and overall reduce Makespan better than Min-min and original Max-min, also achieve of resource utilization and resource usage rate.