Algorithm is Based on Ant Colony Optimization using Grid Simulaor
Tharani R, JCT College of Engineering and Technology, Coimbatore, Tamil Nadu
Grid Computing, Load Balancing, Resource management, Execution time, Execution Cost, Ant Colony Algorithm, Random Algorithm
In today’s competitive environment the objectives and goals of the producers (also called resource owners) and consumers (also called end users) are different. Computational grid has been considered as the best paradigm for handling large scale distributed system having geographically allocated resources. Load balancing algorithms are important in the research of network applications. In this paper we present an algorithm which reduces the average execution time and cost of the tasks. This method considers both cost and time constraints. The proposed algorithm is implemented with Gridsim toolkit which can simulate a decentralized module. The GridSim toolkit abstracts the features and behaviour of complex fundamental grid elements such as grid tasks, grid resources and grid users. This algorithm provides services like resource discovery. For evaluation purpose a comparison of execution times and cost of proposed algorithm and the other similar algorithm is also provided in this paper. Results support the proposed approach.
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Paper ID: GRDCF007042
Published in: Conference : National Conference on Emerging Trends in Electrical, Electronics and Computer Engineering (ETEEC - 2018)
Page(s): 222 - 227
Published in: Conference : National Conference on Emerging Trends in Electrical, Electronics and Computer Engineering (ETEEC - 2018)
Page(s): 222 - 227