Article thumbnail
Location of Repository

Self-organising agent communities for autonomic computing

By Mariusz Jacyno


Efficient resource management is one of key problems associated with large-scale distributed computational systems. Taking into account their increasing complexity, inherent distribution and dynamism, such systems are required to adjust and adapt resources market that is offered by them at run-time and with minimal cost. However, as observed by major IT vendors such as IBM, SUN or HP, the very nature of such systems prevents any reliable and efficient control over their functioning through human administration.<br/><br/>For this reason, autonomic system architectures capable of regulating their own functioning are suggested as the alternative solution to looming software complexity crisis. Here, large-scale infrastructures are assumed to comprise myriads of autonomic elements, each acting, learning or evolving separately in response to interactions in their local environments. The self-regulation of the whole system, in turn, becomes a product of local adaptations and interactions between system elements.<br/><br/>Although many researchers suggest the application of multi-agent systems that are suitable for realising this vision, not much is known about regulatory mechanisms that are capable to achieve efficient organisation within a system comprising a population of locally and autonomously interacting agents. <br/><br/>To address this problem, the aim of the work presented in this thesis was to understand how global system control can emerge out of such local interactions of individual system elements and to develop decentralised decision control mechanisms that are capable to employ this bottom-up self-organisation in order to preserve efficient resource management in dynamic and unpredictable system functioning conditions. To do so, we have identified the study of complex natural systems and their self-organising properties as an area of research that may deliver novel control solutions within the context of autonomic computing.<br/><br/>In such a setting, a central challenge for the construction of distributed computational systems was to develop an engineering methodology that can exploit self-organising principles observed in natural systems. This, in particular, required to identify conditions and local mechanisms that give rise to useful self-organisation of interacting elements into structures that support required system functionality. To achieve this, we proposed an autonomic system model exploiting self-organising algorithms and its thermodynamic interpretation, providing a general understanding of self-organising processes that need to be taken into account within artificial systems exploiting self-organisation.<br/

Topics: QA75
Year: 2010
OAI identifier:
Provided by: e-Prints Soton
Sorry, our data provider has not provided any external links therefore we are unable to provide a link to the full text.

Suggested articles


  1. (1999). A brief history of stigmergy. doi
  2. (1997). Autocatakinetics, evolution, and the law of maximum entropy production: A principled foundation towards the study of human ecology. Advances in Human Ecology,
  3. (2004). Challenges and research directions in agent-oriented software engineering. doi
  4. (2003). Cooperative role-based administration. doi
  5. (2003). Critical critical systems. doi
  6. (2007). Distributed cooperative control for adaptive performance management. doi
  7. (2001). Dyke Parunak. Signs of a revolution in computer science and software engineering. doi
  8. (2004). Dyke Parunak. Towards a paradigm change in computer science and software engineering: A synthesis. doi
  9. (2004). Emergence and self-organisation: a statement of similarities and differences.
  10. (1989). Evolution and thermodynamics: The new paradigm. doi
  11. (1988). Evolution, thermodynamics, and information: Extending the darwinian program. doi
  12. (2000). Improving the scalability of multi-agent systems. doi
  13. (1998). Is the study of complex adaptive systems going to solve the mystery of adam smith’s ”invisible hand”? The Independent Review,
  14. (2001). J2ee vs. A comparison of building xmlbased web services.
  15. (2000). Layered learning and flexible teamwork in robocup simulation agents. doi
  16. (1998). Methods for task allocation via agent coalition formation. doi
  17. (2003). Neurons, viscose fluids, freshwater polyp hydra-and self-organizing information systems. doi
  18. Performance impact of web services on internet servers. doi
  19. (2007). Reinforcement learning in autonomic computing: A manifesto and case studies. doi
  20. (1985). Renesse. Distributed operating systems. doi
  21. (1998). Response threshold reinforcement and division of labour in insect societies. doi
  22. (1999). Robust design through diversity.
  23. (2001). Social inhibition and the regulation of temporal polyethism in honey bees. doi
  24. (2000). The Gaia methodology for agentoriented analysis and design. Autonomous Agents and Multi-Agent Systems, doi
  25. (1991). Thermodynamic reasons for perception-action cycles. doi
  26. (2002). What can cellular automata tell us about the behavior of large multi-agent systems? doi

To submit an update or takedown request for this paper, please submit an Update/Correction/Removal Request.