Agent-based grid load balancing using performance-driven task scheduling

Junwei Cao; Daniel P. Spooner; Stephen A. Jarvis; Subhash Saini; Graham R. Nudd

doi:10.1109/IPDPS.2003.1213139

Agent-based grid load balancing using performance-driven task scheduling

Junwei Cao^*, Daniel P. Spooner, Stephen A. Jarvis, Subhash Saini, Graham R. Nudd

^*Corresponding author for this work

Engineering and Physical Sciences

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

74 Citations (Scopus)

Abstract

Load balancing is a key concern when developing parallel and distributed computing applications. The emergence of computational grids extends this problem, where issues of cross-domain and large-scale scheduling must also be considered. In this paper an agent-based grid management infrastructure is coupled with a performance-driven task scheduler that has been developed for local grid load balancing. Each grid scheduler utilises predictive application performance data and an iterative heuristic algorithm to engineer local load balancing across multiple processing nodes. At a higher level, a hierarchy of homogeneous agents are used to represent multiple grid resources. Agents cooperate with each other to balance workload in the global grid environment using service advertisement and discovery mechanisms. A case study is included with corresponding experimental results to demonstrate that both local schedulers and agents contribute to overall grid load balancing, which significantly improves grid application execution performance and resource utilisation.

Original language	English
Title of host publication	Proceedings - International Parallel and Distributed Processing Symposium, IPDPS 2003
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
ISBN (Electronic)	0769519261, 9780769519265
DOIs	https://doi.org/10.1109/IPDPS.2003.1213139
Publication status	Published - 2003
Event	International Parallel and Distributed Processing Symposium, IPDPS 2003 - Nice, France Duration: 22 Apr 2003 → 26 Apr 2003

Publication series

Name	Proceedings - International Parallel and Distributed Processing Symposium, IPDPS 2003

Conference

Conference	International Parallel and Distributed Processing Symposium, IPDPS 2003
Country/Territory	France
City	Nice
Period	22/04/03 → 26/04/03

Bibliographical note

Publisher Copyright:
© 2003 IEEE.

ASJC Scopus subject areas

Computational Theory and Mathematics
Theoretical Computer Science
Software

Access to Document

10.1109/IPDPS.2003.1213139

Cite this

Cao, J., Spooner, D. P., Jarvis, S. A., Saini, S., & Nudd, G. R. (2003). Agent-based grid load balancing using performance-driven task scheduling. In Proceedings - International Parallel and Distributed Processing Symposium, IPDPS 2003 Article 1213139 (Proceedings - International Parallel and Distributed Processing Symposium, IPDPS 2003). Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/IPDPS.2003.1213139

Cao, Junwei ; Spooner, Daniel P. ; Jarvis, Stephen A. et al. / Agent-based grid load balancing using performance-driven task scheduling. Proceedings - International Parallel and Distributed Processing Symposium, IPDPS 2003. Institute of Electrical and Electronics Engineers (IEEE), 2003. (Proceedings - International Parallel and Distributed Processing Symposium, IPDPS 2003).

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title = "Agent-based grid load balancing using performance-driven task scheduling",

abstract = "Load balancing is a key concern when developing parallel and distributed computing applications. The emergence of computational grids extends this problem, where issues of cross-domain and large-scale scheduling must also be considered. In this paper an agent-based grid management infrastructure is coupled with a performance-driven task scheduler that has been developed for local grid load balancing. Each grid scheduler utilises predictive application performance data and an iterative heuristic algorithm to engineer local load balancing across multiple processing nodes. At a higher level, a hierarchy of homogeneous agents are used to represent multiple grid resources. Agents cooperate with each other to balance workload in the global grid environment using service advertisement and discovery mechanisms. A case study is included with corresponding experimental results to demonstrate that both local schedulers and agents contribute to overall grid load balancing, which significantly improves grid application execution performance and resource utilisation.",

author = "Junwei Cao and Spooner, {Daniel P.} and Jarvis, {Stephen A.} and Subhash Saini and Nudd, {Graham R.}",

note = "Publisher Copyright: {\textcopyright} 2003 IEEE.; International Parallel and Distributed Processing Symposium, IPDPS 2003 ; Conference date: 22-04-2003 Through 26-04-2003",

year = "2003",

doi = "10.1109/IPDPS.2003.1213139",

language = "English",

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Cao, J, Spooner, DP, Jarvis, SA, Saini, S & Nudd, GR 2003, Agent-based grid load balancing using performance-driven task scheduling. in Proceedings - International Parallel and Distributed Processing Symposium, IPDPS 2003., 1213139, Proceedings - International Parallel and Distributed Processing Symposium, IPDPS 2003, Institute of Electrical and Electronics Engineers (IEEE), International Parallel and Distributed Processing Symposium, IPDPS 2003, Nice, France, 22/04/03. https://doi.org/10.1109/IPDPS.2003.1213139

Agent-based grid load balancing using performance-driven task scheduling. / Cao, Junwei; Spooner, Daniel P.; Jarvis, Stephen A. et al.
Proceedings - International Parallel and Distributed Processing Symposium, IPDPS 2003. Institute of Electrical and Electronics Engineers (IEEE), 2003. 1213139 (Proceedings - International Parallel and Distributed Processing Symposium, IPDPS 2003).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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AB - Load balancing is a key concern when developing parallel and distributed computing applications. The emergence of computational grids extends this problem, where issues of cross-domain and large-scale scheduling must also be considered. In this paper an agent-based grid management infrastructure is coupled with a performance-driven task scheduler that has been developed for local grid load balancing. Each grid scheduler utilises predictive application performance data and an iterative heuristic algorithm to engineer local load balancing across multiple processing nodes. At a higher level, a hierarchy of homogeneous agents are used to represent multiple grid resources. Agents cooperate with each other to balance workload in the global grid environment using service advertisement and discovery mechanisms. A case study is included with corresponding experimental results to demonstrate that both local schedulers and agents contribute to overall grid load balancing, which significantly improves grid application execution performance and resource utilisation.

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Cao J, Spooner DP, Jarvis SA, Saini S, Nudd GR. Agent-based grid load balancing using performance-driven task scheduling. In Proceedings - International Parallel and Distributed Processing Symposium, IPDPS 2003. Institute of Electrical and Electronics Engineers (IEEE). 2003. 1213139. (Proceedings - International Parallel and Distributed Processing Symposium, IPDPS 2003). doi: 10.1109/IPDPS.2003.1213139

Agent-based grid load balancing using performance-driven task scheduling

Abstract

Publication series

Conference

Bibliographical note

ASJC Scopus subject areas

Access to Document

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Cite this