A feedback control mechanism for balancing I/O- and memory-intensive applications on clusters

Xiao Qin, Hong Jiang, Yifeng Zhi, David R. Swanson

Research output: Contribution to journalArticlepeer-review

2 Scopus citations


One common assumption of existing models of load balancing is that the weights of resources and I/O buffer size are statically configured and cannot be adjusted based on a dynamic workload. Though the static configuration of these parameters performs well in a cluster where the workload can be modeled and predicted, its performance is poor in dynamic systems in which the workload is unknown. In this paper, a new feedback control mechanism is proposed to improve overall performance of a cluster with a general and practical workload including I/O-intensive and memory-intensive load. This mechanism is also shown to be effective in complementing and enhancing the performance of a number of existing dynamic load-balancing schemes. To capture the current and past workload characteristics, the primary objectives of the feedback mechanism are: (1) dynamically adjusting the resource weights, which indicate the significance of the resources, and (2) minimizing the number of page faults for memory-intensive jobs while increasing the utilization of the I/O buffers for I/O-intensive jobs by manipulating the I/O buffer size. Results from extensive trace-driven simulation experiments show that compared with a number of schemes with fixed resource weights and buffer sizes, the feedback control mechanism delivers a performance improvement in terms of the mean slowdown by up to 282% (with an average of 125%).

Original languageEnglish (US)
Pages (from-to)95-107
Number of pages13
JournalScalable Computing
Issue number4
StatePublished - 2005


  • Cluster
  • Feedback control
  • I/O-intensive applications
  • Load balancing

ASJC Scopus subject areas

  • Computer Science(all)


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