Self-organising agent communities for autonomic resource management


Jacyno, Mariusz, Bullock, Seth, Geard, Nicholas, Payne, Terry R. and Luck, Michael (2013) Self-organising agent communities for autonomic resource management. Adaptive Behavior, 21, (1), 3-28. (doi:10.1177/1059712312462247 ).

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Description/Abstract

The autonomic computing paradigm addresses the operational challenges presented by increasingly complex software systems by proposing that they be composed of many autonomous components, each responsible for the run-time reconfiguration of its own dedicated hardware and software components. Consequently, regulation of the whole software system becomes an emergent property of local adaptation and learning carried out by these autonomous system elements. Designing appropriate local adaptation policies for the components of such systems remains a major challenge. This is particularly true where the system’s scale and dynamism compromise the efficiency of a central executive and/or prevent components from pooling information to achieve a shared, accurate evidence base for their negotiations and decisions.

In this paper, we investigate how a self-regulatory system response may arise spontaneously from local interactions between autonomic system elements tasked with adaptively consuming/providing computational resources or services when the demand for such resources is continually changing. We demonstrate that system performance is not maximised when all system components are able to freely share information with one another. Rather, maximum efficiency is achieved when individual components have only limited knowledge of their peers. Under these conditions, the system self-organises into appropriate community structures. By maintaining information flow at the level of communities, the system is able to remain stable enough to efficiently satisfy service demand in resource-limited environments, and thus minimise any unnecessary reconfiguration whilst remaining sufficiently adaptive to be able to reconfigure when service demand changes.

Item Type: Article
ISSNs: 1059-7123 (print)
Keywords: autonomic computing, networks, self-organisation, community structure, decentralised control, emergence
Subjects: Q Science > QA Mathematics > QA76 Computer software
Divisions: Faculty of Physical Sciences and Engineering > Electronics and Computer Science > Agents, Interactions & Complexity
ePrint ID: 342217
Date Deposited: 16 Aug 2012 08:58
Last Modified: 14 Apr 2014 11:45
Research Funder: EPSRC
Projects:
Amorphous computation, random graphs and complex biological networks
Funded by: EPSRC (EP/D00232X/1)
1 January 2006 to 30 September 2010
Further Information:Google Scholar
ISI Citation Count:0
URI: http://eprints.soton.ac.uk/id/eprint/342217

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