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

Xiao Qin, Hong Jiang, Yifeng Zhu, David R Swanson

Research output: Contribution to journalArticle

14 Citations (Scopus)

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.

Original languageEnglish (US)
Pages (from-to)224-229
Number of pages6
JournalLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume2790
StatePublished - Dec 1 2004

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Dynamic Load Balancing
Dynamic loads
Workload
Feedback Control
Resource allocation
Feedback control
Buffers
Load Balancing
Data storage equipment
Buffer
Weights and Measures
Dynamical systems
Resources
Dynamic Systems
Trace
Unknown
Configuration
Simulation
Model

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

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