A Dynamic Resource Broker and Fuzzy Logic Based Scheduling Algorithm in Grid Environment
ICANNGA '07 Proceedings of the 8th international conference on Adaptive and Natural Computing Algorithms, Part I
The Grid as a Single Entity: Towards a Behavior Model of the Whole Grid
OTM '08 Proceedings of the OTM 2008 Confederated International Conferences, CoopIS, DOA, GADA, IS, and ODBASE 2008. Part I on On the Move to Meaningful Internet Systems:
Evolutionary Fuzzy Scheduler for Grid Computing
IWANN '09 Proceedings of the 10th International Work-Conference on Artificial Neural Networks: Part I: Bio-Inspired Systems: Computational and Ambient Intelligence
An Online and Predictive Method for Grid Scheduling Based on Data Mining and Rough Set
ICCSA '09 Proceedings of the International Conference on Computational Science and Its Applications: Part I
A fuzzy rule-based meta-scheduler with evolutionary learning for grid computing
Engineering Applications of Artificial Intelligence
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This paper presents a grid scheduling optimization technique based on knowledge discovery. The main idea is to transform the grid monitoring data into a performance data set, extract the association patterns of performance data through fuzzy association rule mining, then construct optimization logic according to the mining results, and finally optimize the grid scheduling. In the process of data mining, a method of association rule mining is proposed based on time-window and fuzzy set concepts, which can mine data for quantitative attribute value based on the attribute and time dimensions in grid performance data set.