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Data Grid provides geographically distributed storage resources for large-scale data-intensive applications that generate large data sets. Because data is the important resource in data grids, an efficient management is needed to minimize the response time of applications. Replication is typically used in data grids to improve access time and to reduce the bandwidth consumption. In this paper, we...
Genetic algorithms are becoming increasingly valuable in solving large-scale, realistic, difficult problems, and selecting replica with multiple selection criteria - availability, security and time- is one of these problems. In this paper, a rank based elitist clustering Genetic Algorithm is proposed named RRWSGA, which alleviates the problem of being trapped in local clustering centroids using k-mean...
In this paper, we study the impact of tasks reallocation onto a multi-cluster environment where clusters are heterogeneous and use different resources management policies. In this context, we propose a reallocation mechanism that migrates waiting jobs from one cluster to another. We performed simulations using real traces to study benefits of reallocations. We compared two algorithms providing the...
Grid systems are developed in very dynamic and heterogeneous environments, characterized by an high level of unpredictability. Some system performance, in fact, may vary due to sudden failures or to the occurrence of circumstances unforeseeable deterministically (e.g. failure of the machines, load higher than the expected and inaccuracy in the estimation of parameters). The presence of a robust scheduling...
The ever changing demands on the computational resources have generated the need for solutions that are more flexible. Using a ??bigger box?? that has more and faster processors and permanent storage or more random access memory (RAM) is not a viable solution as the system usage patterns vary. A grid based distributed system can solve this problem by allowing multiple independent jobs to run over...
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