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In order to make the refined process dynamic, it pursues its implementation using Self-Organising Neural Networks. The outcome of this is a Pareto front of optimal strategies, all of which would satisfy the objectives.ArrayThe Capsule Reviews are intended to provide a short succinct review of each paper in the issue in order to bring to a wider readership.. Professor Kamareddine is an Associate Editor of The Computer Journal and is based in the Department of Mathematical and Computer Sciences at Heriot-Watt University, Edinburgh, UK. We demonstrate that in this context, an overlay rewiring process based purely on local decisions and interactions can result in efficient load-balancing without central planning. We show that a ‘secondary’ self-organization process ensues, whereby nodes spontaneously cluster according to their implicit objective.Genetic Algorithms may be used together with Pareto Optimality in the process of selection of an optimal strategy by taking into account this distribution alongside user preferences, video content characteristics and usage history. Finally, we introduce dynamic goals by making the preferred neighbour type a function of the local characteristics of a simulated workload. Scalability issues with respect to the key parameters of system size and diversity are extensively discussed.In this paper, we investigate the global self-aggregation dynamics arising from local decision-based rewiring of an overlay network, used as an abstraction for an autonomic service-oriented architecture. The Capsule Reviews were compiled by Fairouz Kamareddine. The distribution of optimal strategies on a Pareto front, however, suggests that there may be a ‘best-fit’ optimal strategy. We conclude

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