Abstract
The emerging computational grid infrastructure consists of heterogeneous resource in widely distributed autonomous domains, which makes resource scheduling even more challenging. In this paper, we propose an adaptive resource scheduling algorithm for computational grid called BLBD (based on load balancing and demand). According to the computational grid job's personal resource requirements, the system load of computational grid nodes and the load balancing of computational grid system, the algorithm choose an appropriate node self adaptively for computational grid job from the candidates. It has been successfully tested in NPU campus computational grid environment. The experimental result shows that the new task scheduling algorithm can lead to significant performance gain for a variety of applications
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