Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2004.Includes bibliographical references (p. 92-95).(cont.) down implicit assumptions of altruism while showing the resulting negative impact on utility. From a selfish equilibrium, with much lower global utility, we show the ability of our algorithm to reorganize and restore the utility of individual nodes, and the system as a whole, to similar levels as realized in the SuperPeer network. Simulation of our algorithm shows that it reaches the predicted optimal utility while providing fairness not realized in other systems. Further analysis includes an epsilon equilibrium model where we attempt to more accurately represent the actual reward function of nodes. We find that by employing such a model, over 60% of the nodes are connected. In addition, this model converges to a utility 34% greater than achieved in the SuperPeer network while making no assumptions on the benevolence of nodes or centralized organization.This thesis proposes a reorganization algorithm, based on the region abstraction, to exploit the natural structure in overlays that stems from common interests. Nodes selfishly adapt their connectivity within the overlay in a distributed fashion such that the topology evolves to clusters of users with shared interests. Our architecture leverages the inherent heterogeneity of users and places within the system their incentives and ability to affect the network. As such, it is not dependent on the altruism of any other nodes in the system. Of particular interest is the optimality and fairness of our design. We rigorously define ideal and fair networks and develop a continuum of optimality measures by which to evaluate our algorithm. Further, to evaluate our algorithm within a realistic context, validate assumptions and make design decisions, we capture data from a portion of a live file-sharing network. More importantly, we discover, name, quantify and solve several previously unrecognized subtle problems in a content-based self-organizing network as a direct result of simulations using the trace data. We motivate our design by examining the dependence of existing systems on benevolent Super-Peers. Through simulation we find that the current architecture is highly dependent on the filtering capability and the willingness of the SuperPeer network to absorb the majority of the query burden. The remainder of the thesis is devoted to a world in which SuperPeers no longer exist or are untenable. In our evaluation, we introduce four reasons for utility suboptimal self-reorganizing networks: anarchy (selfish behavior), indifference, myopia and ordering. We simulate the level of utility and happiness achieved in existing architectures. Then we systematically tearby Robert E. Beverly, IV.S.M
