A foundational issue underlying many overlay network applications ranging from routing to peer-to-peer file sharing is that of the network formation, i.e., folding new arrivals into an existing overlay, and rewiring to cope with changing network conditions. Previous work has considered the problem from two perspectives: devising practical heuristics for the case of cooperative peers and performing game-theoretic analysis for the case of selfish peers. In this paper, we unify the aforementioned thrusts by defining and studying the selfish neighbor selection (SNS) game and its application to overlay routing. At the heart of SNS stands the restriction that peers are allowed up to a certain number of neighbors. This makes SNS substantially different from existing network formation games that impose no bounds on peer degrees. Having bounded degrees has important practical consequences as it permits the creation of overlay structures that requireO(n) instead ofO(n2) link monitoring overhead. We show that a node's “best response” wiring strategy amounts to solving ak-median problem on asymmetric distance. Best-response wirings have substantial practical utility as they permit selfish nodes to reap substantial performance benefits when connecting to overlays of nonselfish nodes. A more intricate consequence is that even nonselfish nodes can benefit from the existence of some selfish nodes since the latter, via their local optimizations, create a highly optimized backbone, upon which even simple heuristic wirings yield good performance. To capitalize on the above properties, we design, build, and deploy EGOIST, an SNS-inspired prototype overlay routing system for PlanetLab. We demonstrate that EGOIST outperforms existing heuristic overlays on a variety of performance metrics, including delay, available bandwidth, and node utilization, while it remains competitive with an optimal but unscalable full-mesh overlay.

A foundational issue underlying many overlay network applications ranging from routing to peer-to-peer file sharing is that of connectivity management, i.e., folding new arrivals into an existing overlay, and re-wiring to cope with changing network conditions. Previous work has considered the problem from two perspectives: devising practical heuristics for specific applications designed to work well in real deployments, and providing abstractions for the underlying problem that are analytically tractable, especially via game-theoretic analysis. In this paper, we unify these two thrusts by using insights gleaned from novel, realistic theoretic models in the design of EGOIST -- a distributed overlay routing system that we implemented, deployed, and evaluated on PlanetLab. Using extensive measurements of paths between nodes, we demonstrate that EGOIST'S neighbor selection primitives significantly outperform existing heuristics on a variety of performance metrics, including delay, available bandwidth, and node utilization. Moreover, we demonstrate that EGOIST is competitive with an optimal, but unscalable full-mesh approach, remains highly effective under significant churn, is robust to cheating, and incurs minimal overhead. Finally, we use a multiplayer peer-to-peer game to demonstrate the value of EGOIST to end-user applications.