Dynamic load balancing for I/O- and memory-intensive workload in clusters using a feedback control mechanism

Abstract

One common assumption of the existing models of load balancing is that the weights of resources and I/O buffer size are statically configured. Though the static configuration of these parameters performs well in a cluster where the workload can be predicted, its performance is poor in dynamic systems where the workload is unknown. In this paper, a new feedback control mechanism is proposed to improve the overall performance of a cluster with I/O-intensive and memory-intensive workload. The mechanism dynamically adjusts the resource weights as well as the I/O buffer size. Results from a trace-driven simulation show that this mechanism is effective in enhancing the performance of a number of existing load-balancing schemes. © Springer-Verlag 2003.