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Load balancing techniques play a critically important role in developing high-performance cluster computing platforms. Existing load balancing approaches are concerned with the effective usage of CPU and memory resources. Due to imbalance in disk I/O resources under I/O-intensive workloads, the previous CPU- or memory-aware load balancing schemes suffer significant performance drop. To remedy this deficiency, in this paper the authors propose a novel load-balancing algorithm (hereinafter referred to as IOLB) for clusters, which aims at maintaining high resource utilization under a wide range of workload conditions.
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