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We measure the ability of a selected set of local rules to foster self-organization of what is originally a random graph into a structured network. We show that a ‘secondary’ self-organization process ensues, whereby nodes spontaneously cluster according to their implicit objective. 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. Conflicting goals are introduced, in the form of a population of nodes actively seeking to acquire neighbours of a type different from their own, resulting in decreased local homogeneity. The distribution of optimal strategies on a Pareto front, however, suggests that there may be a ‘best-fit’ optimal strategy.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. We conclude by discussing the implications of our findings for the design of future distributed applications, the likely influence of other factors and of extreme parameter values on the ability of the system to self-organize and the potential improvements to our framework.. 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. Finally, we introduce dynamic goals by making the preferred neighbour type a function of the local characteristics of a simulated workload.In

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