On decentralised clustering in self-monitoring networks

Piraveenan Mahendra Rajah; Mikhail Prokopenko; Peter Wang; Don Price

On decentralised clustering in self-monitoring networks

Piraveenan Mahendra Rajah, Mikhail Prokopenko^*, Peter Wang, Don Price

^*Corresponding author for this work

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

Abstract

A Decentralised Adaptive Clustering (DAC) algorithm for multiagent networks is contrasted with a Fixed-order Centralised Adaptive Clustering algorithm (FCAC). The clustering is done on sensor readings detected within a self-monitoring impact sensing network. Simulation results show that DAC algorithm scales well with increasing network and data sizes and in some cases outperforms FCAC algorithm. While the common-sense intuition suggests that centralised algorithm is always superior, we support the simulation results with a simple counter-example.

Original language	English
Title of host publication	Proceedings of the 4th International Conference on Autonomous Agents and Multi agent Systems, AAMAS 05
Editors	F. Dignum, V. Dignum, S. Koenig, S. Kraus, M. Pechoucek, M. Singh, D. Steiner, S. Thompson, M. Wooldridge
Place of Publication	New York
Publisher	ACM
Pages	1279-1280
Number of pages	2
ISBN (Electronic)	1595930930, 9781595930934
Publication status	Published - 2005
Externally published	Yes
Event	4th International Conference on Autonomous Agents and Multi agent Systems, AAMAS 05 - Utrecht, Netherlands Duration: 25 Jul 2005 → 29 Jul 2005

Other

Other	4th International Conference on Autonomous Agents and Multi agent Systems, AAMAS 05
Country/Territory	Netherlands
City	Utrecht
Period	25/07/05 → 29/07/05

Keywords

Clustering
Scalability
Sensor networks

Cite this

Rajah, Piraveenan Mahendra ; Prokopenko, Mikhail ; Wang, Peter et al. / On decentralised clustering in self-monitoring networks. Proceedings of the 4th International Conference on Autonomous Agents and Multi agent Systems, AAMAS 05. editor / F. Dignum ; V. Dignum ; S. Koenig ; S. Kraus ; M. Pechoucek ; M. Singh ; D. Steiner ; S. Thompson ; M. Wooldridge. New York : ACM, 2005. pp. 1279-1280

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abstract = "A Decentralised Adaptive Clustering (DAC) algorithm for multiagent networks is contrasted with a Fixed-order Centralised Adaptive Clustering algorithm (FCAC). The clustering is done on sensor readings detected within a self-monitoring impact sensing network. Simulation results show that DAC algorithm scales well with increasing network and data sizes and in some cases outperforms FCAC algorithm. While the common-sense intuition suggests that centralised algorithm is always superior, we support the simulation results with a simple counter-example.",

keywords = "Clustering, Scalability, Sensor networks",

author = "Rajah, {Piraveenan Mahendra} and Mikhail Prokopenko and Peter Wang and Don Price",

year = "2005",

language = "English",

pages = "1279--1280",

editor = "F. Dignum and V. Dignum and S. Koenig and S. Kraus and M. Pechoucek and M. Singh and D. Steiner and S. Thompson and M. Wooldridge",

booktitle = "Proceedings of the 4th International Conference on Autonomous Agents and Multi agent Systems, AAMAS 05",

publisher = "ACM",

note = "4th International Conference on Autonomous Agents and Multi agent Systems, AAMAS 05 ; Conference date: 25-07-2005 Through 29-07-2005",

}

Rajah, PM, Prokopenko, M, Wang, P & Price, D 2005, On decentralised clustering in self-monitoring networks. in F Dignum, V Dignum, S Koenig, S Kraus, M Pechoucek, M Singh, D Steiner, S Thompson & M Wooldridge (eds), Proceedings of the 4th International Conference on Autonomous Agents and Multi agent Systems, AAMAS 05. ACM, New York, pp. 1279-1280, 4th International Conference on Autonomous Agents and Multi agent Systems, AAMAS 05, Utrecht, Netherlands, 25/07/05.

On decentralised clustering in self-monitoring networks. / Rajah, Piraveenan Mahendra; Prokopenko, Mikhail; Wang, Peter et al.
Proceedings of the 4th International Conference on Autonomous Agents and Multi agent Systems, AAMAS 05. ed. / F. Dignum; V. Dignum; S. Koenig; S. Kraus; M. Pechoucek; M. Singh; D. Steiner; S. Thompson; M. Wooldridge. New York: ACM, 2005. p. 1279-1280.

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

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AU - Rajah, Piraveenan Mahendra

AU - Prokopenko, Mikhail

AU - Wang, Peter

AU - Price, Don

PY - 2005

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N2 - A Decentralised Adaptive Clustering (DAC) algorithm for multiagent networks is contrasted with a Fixed-order Centralised Adaptive Clustering algorithm (FCAC). The clustering is done on sensor readings detected within a self-monitoring impact sensing network. Simulation results show that DAC algorithm scales well with increasing network and data sizes and in some cases outperforms FCAC algorithm. While the common-sense intuition suggests that centralised algorithm is always superior, we support the simulation results with a simple counter-example.

AB - A Decentralised Adaptive Clustering (DAC) algorithm for multiagent networks is contrasted with a Fixed-order Centralised Adaptive Clustering algorithm (FCAC). The clustering is done on sensor readings detected within a self-monitoring impact sensing network. Simulation results show that DAC algorithm scales well with increasing network and data sizes and in some cases outperforms FCAC algorithm. While the common-sense intuition suggests that centralised algorithm is always superior, we support the simulation results with a simple counter-example.

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KW - Scalability

KW - Sensor networks

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EP - 1280

BT - Proceedings of the 4th International Conference on Autonomous Agents and Multi agent Systems, AAMAS 05

A2 - Dignum, F.

A2 - Dignum, V.

A2 - Koenig, S.

A2 - Kraus, S.

A2 - Pechoucek, M.

A2 - Singh, M.

A2 - Steiner, D.

A2 - Thompson, S.

A2 - Wooldridge, M.

PB - ACM

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T2 - 4th International Conference on Autonomous Agents and Multi agent Systems, AAMAS 05

Y2 - 25 July 2005 through 29 July 2005

ER -

On decentralised clustering in self-monitoring networks

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