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A new method for the informed discovery of resources in the grid system using particle swarm optimization algorithm (RDT_PSO)

机译:一种新的使用粒子群优化算法(RDT_PSO)的网格系统资源发现方法

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Nowadays, there has been a growing interest in investigating and improving the methods used for resource discovery and access in grid systems, the reason could be the important role of resource exploration methods in determining the quality and performance of grid systems. With the development of grid environments and the increase in the number of resources and geographical distribution, finding new algorithms to discover the required resources at a minimized resource discovery timespan is considered an important task. In this study, by using the intelligent resource discovery model as well as the decentralized method, it is shown that the optimal resource may be searched for reservation and allocation with the least number of visited nodes and the minimum time possible. In order to find the quickest path, the proposed algorithm was optimized using the particle swarm optimization algorithm; then it was compared to the BITMAP and Footprint Resource Discovery Tree, which are among the hierarchical methods of resource discovery. According to the results, the number of visited nodes in the proposed method was found be lower than those of other methods.
机译:如今,人们对研究和改进用于网格系统中资源发现和访问的方法的兴趣与日俱增,其原因可能是资源探索方法在确定网格系统的质量和性能方面的重要作用。随着网格环境的发展以及资源数量和地理分布的增加,寻找新的算法以在最小的资源发现时间范围内发现所需资源被认为是一项重要的任务。在这项研究中,通过使用智能资源发现模型以及分散方法,表明可以在访问节点数量最少,时间最少的情况下搜索最佳资源进行预留和分配。为了找到最快的路径,使用粒子群算法对提出的算法进行了优化。然后将其与BITMAP和足迹资源发现树进行比较,后者是资源发现的分层方法。结果表明,该方法的访问节点数少于其他方法。

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