Abstract
Cloud computing is being welcomed as a new basis to manage and provide services on the internet. One of the reasons for increased efficiency of this environment is the appropriate structure of the tasks scheduler. Since the tasks scheduling in the cloud computing environment and distributed systems is an NP-hard problem, in most cases to optimize the scheduling issues, the meta-heuristic methods inspired by nature are used rather than traditional or greedy methods. One of the most powerful meta-heuristic methods of optimization in the complex problems is an Imperialist Competitive Algorithm (ICA). Thus, in this paper, a meta-heuristic method based on ICA is provided to optimize the scheduling issue in the cloud environment. Simulation results in MATLAB environment show the amount of 0.7 percent improvement in execution time compared with a Genetic Algorithm(GA).
Highlights
Today, data centers are composed of thousands of computers that are distributed worldwide and users use the computers frequently to send e-mail, read, write, search, etc
The results showed an improvement in performance of the proposed algorithm comparing to the other methods proposed for tasks scheduling in the cloud environment such as GAs, particle swarm, and the standard Imperialist Competitive Algorithm (ICA)
In most of the algorithms provided for mapping the tasks to resources in cloud environment, only attention is given to the time of performing tasks and bandwidth features of resources and time of sending tasks are not considered as effective parameters in producing the final answer
Summary
Data centers are composed of thousands of computers that are distributed worldwide and users use the computers frequently to send e-mail, read, write, search, etc. Cloud computing [1, 2, 3, 4, 5] combines parallel concepts and computing systems to provide for computers and other machines shared resources, hardware, software and information [6, 7, 8, 9]. As the allocation of processor and resource to tasks is a complex issue in heterogeneous distributed systems such as cloud environment, many methods and algorithms have been provided to reduce time complexity and simultaneous function of subtasks. Some of the available challenges in the field of scheduling tasks in heterogeneous distributing systems include heterogeneous resources, total running time, runtime and productivity convergence speed in meta-heuristic methods and efficiency of scheduling method. According to the importance of this issue, in this paper, research has been conducted in the field of scheduling computing tasks on cloud computing and heterogeneous systems. In the last section the conclusion and future work are presented
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
