An autonomous performance control framework for distributed multi-agent systems: A queueing theory based approach

Nathan Gnanasambandam; Seokcheon Lee; Soundar R.T. Kumara; Natarajan Gautam; Wilbur Peng; Vikram Manikonda; Marshall Brinn; Mark Greaves

An autonomous performance control framework for distributed multi-agent systems: A queueing theory based approach

Nathan Gnanasambandam, Seokcheon Lee, Soundar R.T. Kumara, Natarajan Gautam, Wilbur Peng, Vikram Manikonda, Marshall Brinn, Mark Greaves

Research output: Contribution to conference › Paper › peer-review

2 Scopus citations

Abstract

Distributed Multi-Agent Systems (DMAS) such as supply chains functioning in highly dynamic environments need to achieve maximum overall utility during operation. The utility from maintaining performance is an important component of their survivability. This utility is often met by identifying trade-offs between quality of service and performance. To adaptively choose the operational settings for better utility, we propose an autonomous and scalable queueing theory based methodology to control the performance of a hierarchical network of distributed agents.

Original language	English (US)
Pages	1391-1392
Number of pages	2
State	Published - 2005
Event	4th International Conference on Autonomous Agents and Multi agent Systems, AAMAS 05 - Utrecht, Netherlands Duration: Jul 25 2005 → Jul 29 2005

Other

Other	4th International Conference on Autonomous Agents and Multi agent Systems, AAMAS 05
Country/Territory	Netherlands
City	Utrecht
Period	7/25/05 → 7/29/05

All Science Journal Classification (ASJC) codes

General Engineering

Cite this

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title = "An autonomous performance control framework for distributed multi-agent systems: A queueing theory based approach",

abstract = "Distributed Multi-Agent Systems (DMAS) such as supply chains functioning in highly dynamic environments need to achieve maximum overall utility during operation. The utility from maintaining performance is an important component of their survivability. This utility is often met by identifying trade-offs between quality of service and performance. To adaptively choose the operational settings for better utility, we propose an autonomous and scalable queueing theory based methodology to control the performance of a hierarchical network of distributed agents.",

author = "Nathan Gnanasambandam and Seokcheon Lee and Kumara, {Soundar R.T.} and Natarajan Gautam and Wilbur Peng and Vikram Manikonda and Marshall Brinn and Mark Greaves",

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Gnanasambandam, N, Lee, S, Kumara, SRT, Gautam, N, Peng, W, Manikonda, V, Brinn, M & Greaves, M 2005, 'An autonomous performance control framework for distributed multi-agent systems: A queueing theory based approach', Paper presented at 4th International Conference on Autonomous Agents and Multi agent Systems, AAMAS 05, Utrecht, Netherlands, 7/25/05 - 7/29/05 pp. 1391-1392.

An autonomous performance control framework for distributed multi-agent systems: A queueing theory based approach. / Gnanasambandam, Nathan; Lee, Seokcheon; Kumara, Soundar R.T. et al.
2005. 1391-1392 Paper presented at 4th International Conference on Autonomous Agents and Multi agent Systems, AAMAS 05, Utrecht, Netherlands.

Research output: Contribution to conference › Paper › peer-review

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AU - Gnanasambandam, Nathan

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AU - Kumara, Soundar R.T.

AU - Gautam, Natarajan

AU - Peng, Wilbur

AU - Manikonda, Vikram

AU - Brinn, Marshall

AU - Greaves, Mark

PY - 2005

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AB - Distributed Multi-Agent Systems (DMAS) such as supply chains functioning in highly dynamic environments need to achieve maximum overall utility during operation. The utility from maintaining performance is an important component of their survivability. This utility is often met by identifying trade-offs between quality of service and performance. To adaptively choose the operational settings for better utility, we propose an autonomous and scalable queueing theory based methodology to control the performance of a hierarchical network of distributed agents.

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M3 - Paper

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An autonomous performance control framework for distributed multi-agent systems: A queueing theory based approach

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All Science Journal Classification (ASJC) codes

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