Dynamic Load Balancing for I/O-Intensive Applications on Clusters

Load balancing for clusters has been investigated extensively, mainly focusing on the effective usage of global CPU and memory resources. However, previous CPU- or memory-centric load balancing schemes suffer significant performance drop under I/O-intensive workloads due to the imbalance of I/O load. To solve this problem, the authors propose two simple yet effective I/O-aware load-balancing schemes for two types of clusters: homogeneous clusters where nodes are identical and heterogeneous clusters, which are comprised of a variety of nodes with different performance characteristics in computing power, memory capacity, and disk speed.