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Accurate grid resources prediction is crucial for a grid scheduler. In this study, support vector regression (SVR), which is an effective regression algorithm, is applied to grid resource prediction. In order to obtain better prediction performance, SVR's parameters must be selected carefully. Therefore, a particle swarm optimization-based SVR (PSO-SVR) model, in which PSO is used to determine free...
Most of the existing intrusion detection system security visualization in which alarms are statistically analyzed and their quantity and distribution are usually represented using 2D/3D charts, some studies have shown that intrusion detection scene visualization is perhaps more effective. The contributions of this paper mainly focus on one aspect, we present a realtime intrusion detection security...
One of the challenging problems in grid environment is the choice of destination nodes where the tasks of the application are to be executed. Therefore, resource prediction is a crucial direction for job scheduling system and grid users. In this paper, Nu-support vector regression (v-SVR) is applied to solve resource prediction problem. The method of parallel multidimensional step search is also introduced...
The computing grid is becoming the platform of choice for large-scale distributed data-intensive applications. Performance measurement, analysis and prediction have become increasingly important in a grid environment, mainly due to resource's geographic distribution, heterogeneity, dynamic, distributed ownership with different policies and priorities, varying loads, reliability, and availability conditions...
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