Ivanoe De Falco
ABSTRACT
To execute large scale applications exploiting the unemployed aggregated power available on grid nodes, effective and efficient mapping algorithms must be designed. Since the problem of optimally mapping is NP--complete, heuristic techniques can be profitably adopted to find near--optimal solutions. Here a multiobjective Differential Evolution algorithm is implemented and tested on different mapping scenarios with the aim to fulfill several optimization criteria. The results attained show the robustness of the evolutionary approach proposed in dealing with multisite grid mapping.
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Index Terms
- An innovative perspective on mapping in grids
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Reviews
Luminita State
The research presented in this paper focuses on adapting, implementing, and testing a variant of the multiobjective differential evolution (DE) algorithm proposed by Storn and Price in 1997 [1], for solving grid scheduling tasks. The introductory section supplies certain considerations concerning the task-to-node allocation and task scheduling problems, as well as comments on current research and trends in the area. The DE algorithm is briefly presented in the second section of the paper. In the first part of Section 3, De Falco et al. describe the parameters of the proposed mapping model and a series of means to overcome the difficulties that arise when deriving suitable parameter settings. Aiming to develop an evolutionary-based approach in the search for an optimal mapping, the second part of this section presents the details of encoding the mapping solutions, the recombination operators, and the fitness criteria. The optimality of the mapping solutions is defined in terms of two fitness functions-expressing the amount of time the grid resources are used and their reliability-and the optimal mapping results, as a solution computed by a multiobjective DE approach. The performance of the proposed method is tested by simulations on a grid architecture that aggregates 184 nodes grouped into six sites. The tests performed and the results obtained are described in Section 4. The first set of tests is carried out on a ring structure application that consists of 16 tasks and on a master-slave application that consists of 31 tasks. The results obtained are promising, and confirm the potential of evolutionary-based approaches in solving the grid multisite mapping problem. Online Computing Reviews Service
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