High Performance Dynamic Load Balancing With Inter-Dependent Tasks And Dependent Tasks in Cloud Computing Environments

Cloud computing is an entirely internet-based approach where all the applications and files are hosted on a cloud which consists of thousands of computers interlinked together in a complex manner. A load balancing algorithm attempts to improve the response time of user’s submitted applications by ensuring maximal utilization of available resources. The main objective of load balancing methods is to speed up the execution of applications on resources whose workload varies at run time in unpredictable way. Load balancing of non preemptive independent tasks on virtual machines (VMs) is an important aspect of task scheduling in clouds. Whenever certain VMs are overloaded and remaining VMs are under loaded with tasks for processing, the load has to be balanced to achieve optimal machine utilization. Previous work Propose an algorithm named honey bee behavior inspired load balancing (HBB-LB), which aims to achieve well balanced load across virtual machines for maximizing the throughput. But the major problem of this work well for independent task and it doesn’t work well for dependent task. Improve the results of the existing bee colony optimization methods, in this work proposed a novel modified artificial bee colony algorithm which supports for dependent and independent task with modified artificial bee colony algorithm for load balancing tasks. The effectiveness of the proposed Modified Artificial Bee Colony for load balancing dependent and independent tasks (MABC-LBDIID) algorithms in reducing the operational cost of the cloud system is demonstrated by comparing the results with existing HBB-LB .The proposed algorithm also balances the priorities of tasks on the machines in such a way that the amount of waiting time of the tasks in the queue is minimal.