Autonomic Computing, International Conference on (2004)
New York, New York
May 17, 2004 to May 18, 2004
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICAC.2004.29
Richard John Anthony , University of Greenwich
<p>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.</p> <p>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.</p> <p>This paper discusses ways in which emergence science can be applied to distributed computing, avoiding some of the compromises associated with traditionally-designed applications.</p> <p>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.</p>
Emergence, Distributed Systems, Fault Tolerance, Scalability, Self-Stabilisation, Election Algorithm
R. J. Anthony, "Emergence: A Paradigm for Robust and Scalable Distributed Applications," Autonomic Computing, International Conference on(ICAC), New York, New York, 2004, pp. 132-139.