Parameter Selection in Particle Swarm Optimization
EP '98 Proceedings of the 7th International Conference on Evolutionary Programming VII
Reliability Analysis of Grid Computing Systems
PRDC '02 Proceedings of the 2002 Pacific Rim International Symposium on Dependable Computing
The Grid 2: Blueprint for a New Computing Infrastructure
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Ordinal Optimization: Soft Computing for Hard Problems (International Series on Discrete Event Dynamic Systems)
A Hierarchical Modeling and Analysis for Grid Service Reliability
IEEE Transactions on Computers
Heuristic solutions to resource allocation in grid computing: a natural approach
The Journal of Supercomputing
Expert Systems with Applications: An International Journal
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ICN '09 Proceedings of the 2009 Eighth International Conference on Networks
Ordinal Optimization and Quantification of Heuristic Designs
Discrete Event Dynamic Systems
Ant colony optimization algorithm with mutation mechanism and its applications
Expert Systems with Applications: An International Journal
A novel set-based particle swarm optimization method for discrete optimization problems
IEEE Transactions on Evolutionary Computation
Dominance-Based Multiobjective Simulated Annealing
IEEE Transactions on Evolutionary Computation
A New Evolutionary Algorithm for Solving Many-Objective Optimization Problems
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A Heuristic Algorithm for Reliability Modeling and Analysis of Grid Systems
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
An improved ant colony optimization for the communication network routing problem
Mathematical and Computer Modelling: An International Journal
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Artificial Life and Robotics
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In this paper, we have formulated the resource allocation optimization problem for expanding service and increasing reliability of a grid computing system. The formulated problem is a combinational optimization as well as an NP-hard problem. We firstly decompose this problem into a minimizing budget problem and a maximizing reliability problem. An approximate model is proposed to estimate the service reliability of a resource allocation design within a tolerable computation time. Secondly, we employ an ordinal optimization (OO) based approach to solve the maximizing reliability problem and a bisection method to solve the minimizing budget problem. The proposed OO based approach consists of two stages. A binary particle swarm optimization (BPSO) algorithm is employed in the first stage using the approximate model for fitness evaluation and selects a subset of good enough solutions. Then we proceed with the goal softening searching procedure in the second stage using more refined approximate models to search for a good enough solution from the subset obtained in the first stage. We have demonstrated the test results by the simulation on a 16-node and 25-link large grid computing system including two resource-managing nodes. We used 8 bisection iterations that consumed 20 minutes to obtain a good enough resource allocation design and the corresponding minimum budget. To test the optimality of the solutions obtained by our approach, we also solved the maximizing reliability problem using two competing methods, the GA and classical BPSO algorithm. The good enough solution obtained by the proposed approach is promising in the aspects of solution quality and computational efficiency.