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.
|Original language||English (US)|
|Number of pages||6|
|Journal||Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|
|State||Published - 2004|
ASJC Scopus subject areas
- Theoretical Computer Science
- Computer Science(all)