A Multi-Objective Deadline-Constrained Task Scheduling Algorithm with Guaranteed Performance in Load Balancing on Heterogeneous Networks

2021 ◽  
Vol 2 (5) ◽  
Author(s):  
Moumita Chatterjee ◽  
S. K. Setua
Author(s):  
Shailendra Raghuvanshi ◽  
Priyanka Dubey

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. In this paper, we propose an algorithm named honey bee behavior inspired load balancing, which aims to achieve well balanced load across virtual machines for maximizing the throughput. 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. We have compared the proposed algorithm with existing load balancing and scheduling algorithms. The experimental results show that the algorithm is effective when compared with existing algorithms. Our approach illustrates that there is a significant improvement in average execution time and reduction in waiting time of tasks on queue using workflowsim simulator in JAVA.


2014 ◽  
Vol 577 ◽  
pp. 935-938
Author(s):  
Cheng Yu Cai ◽  
Yuan Sheng Lou

In order to make up for the shortage of Min-Min in load balancing, a new task scheduling algorithm T-Max-Int Under the grid computing has been proposed in this paper. In T-Max-Int, the Loss Degree of Max-Int has been brought into Min-Min. T was in the form of percentage, which represents the proportion of selected tasks that have loss degree in the total tasks. Then, experiments of T have been taken to make Makespan the minimum. Finally, T-Max-Int, Max-Min, Min-Min were compared, which proved that T-Max-Min is better than the other two algorithms in aspects of Makespan and load balancing.


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