"Selfish Overlay Network Creation and Maintenance"
Georgios Smaragdakis, Nikolaos Laoutaris, Vassilis Lekakis, Azer Bestavros, John W. Byers, and Mema Roussopoulos.
IEEE/ACM Transactions on Networking, 19(6), 2011.

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 re-wiring 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 our work, 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 require O(n) instead of O(n^2) link monitoring overhead.

We show that a node's ``best response" wiring strategy amounts to solving a k-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 non-selfish nodes. A more intricate consequence is that even non-selfish 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.

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