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On scheduling transactions in a grid processing system considering load through Ant Colony Optimization
Affiliation:1. Department of Computer Science and Engineering, Faculty of Electronic Engineering, Menoufia University, Menouf 32952, Egypt;2. Department of Information Technology, College of Computers and Information Technology, Taif University, Al-Hawiya 21974, Kingdom of Saudi Arabia;1. Ecole Polytechnique, Université Paris-Saclay, France;2. Sorbonne Universités, Université de Technologie de Compiègne, CNRS, Heudiasyc, Centre de recherche Royallieu, CS 60 319, 60 203 Compiègne cedex, France;1. College of Information Engineering, Qingdao University, Qingdao 266071, China;2. Weifang University of Science & Technology, Weifang 262700, China;3. Shandong Provincial Key Laboratory of Software Engineering, Ji’nan 250101, China;4. Department of Computer Science, University of Texas at Dallas, TX 75083-0688, USA;5. College of Computer Science, Chongqing University, Chongqing 400044, China
Abstract:Load balanced transaction scheduling problem is an important issue in distributed computing environments including grid system. This problem is known to be NP-hard and can be solved by using heuristic as well as any meta-heuristic method. We ponder over the problem of the load balanced transaction scheduling in a grid processing system by using an Ant Colony Optimization for load balancing. The problem that we consider is to achieve good execution characteristics for a given set of transactions that has to be completed within their given deadline. We propose a transaction processing algorithm based on Ant Colony Optimization (ACO) for load balanced transaction scheduling. We modify two meta-heuristic along with ACO and three heuristic scheduling algorithms for the purpose of comparison with our proposed algorithm. The results of the comparison show that the proposed algorithm provides better results for the load balanced transaction scheduling in the grid processing system.
Keywords:Grid processing system  Load balanced transaction scheduling  Ant Colony Optimization
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