Self-organization algorithms for autonomic systems in the SelfLet approach
Proceedings of the 1st international conference on Autonomic computing and communication systems
Intelligent agents: are they feasible in Swarm-array computing?
ICCOMP'09 Proceedings of the WSEAES 13th international conference on Computers
Achieving intelligent agents and its feasibility in swarm-array computing?
WSEAS Transactions on Computers
Incorporating prediction models in the SelfLet framework: a plugin approach
Proceedings of the Fourth International ICST Conference on Performance Evaluation Methodologies and Tools
An agent-based methodology for self-* systems
Multiagent and Grid Systems
Robustness and scalability: a dual challenge for autonomic architectures
Proceedings of the Fourth European Conference on Software Architecture: Companion Volume
Proceedings of the ACM international conference companion on Object oriented programming systems languages and applications companion
A metabolic approach to protocol resilience
WAC'04 Proceedings of the First international IFIP conference on Autonomic Communication
A scheduling strategy for a real-time dependable organic middleware
SAMOS'06 Proceedings of the 6th international conference on Embedded Computer Systems: architectures, Modeling, and Simulation
Development of self-organising emergent applications with simulation-based numerical analysis
ESOA'05 Proceedings of the Third international conference on Engineering Self-Organising Systems
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Natural distributed systems are adaptive, scalable and fault-tolerant. Emergence science describes how higher-level self-regulatory behaviour arises in natural systems from many participants following simple rule-sets. Emergence advocates simple communication models, autonomy and independence, enhancing robustness and self-stabilization. High-quality distributed applications such as autonomic systems must satisfy the appropriate non-functional requirements which include scalability, efficiency, robustness, low-latency and stability. However the traditional design of distributed applications, especially in terms of the communication strategies employed, can introduce compromises between these characteristics. This paper discusses ways in which emergence science can be applied to distributed computing, avoiding some of the compromises associated with traditionally-designed applications. To demonstrate the effectiveness of this paradigm, an emergent election algorithm is described and its performance evaluated. The design incorporates non-deterministic behaviour. The resulting algorithm has very low communication complexity, and is simultaneously very stable, scalable and robust.