aocbug2

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. The distribution of optimal strategies on a Pareto front, however, suggests that there may be a ‘best-fit’ optimal strategy. The outcome of this is a Pareto front of optimal strategies, all of which would satisfy the objectives. This article refines the process of selection of an optimal strategy by taking into account this distribution alongside user preferences, video content characteristics and usage history. We show that a ‘secondary’ self-organization process ensues, whereby nodes spontaneously cluster according to their implicit objective. The Capsule Reviews were compiled by Fairouz Kamareddine. 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. 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