A Least-Resistance Path in Reasoning about Unstructured Overlay Networks
Unstructured overlay networks for peer-to-peer applications combined with stochastic algorithms for clustering and resource location are attractive due to low-maintenance costs and inherent fault-tolerance and self-organizing properties. Moreover, there is a relatively large volume of experimental evidence that these methods are efficiency-wise a good alternative to structured methods, which require more sophisticated algorithms for maintenance and fault tolerance. However, currently there is a very limited selection of appropriate tools to use in systematically evaluating performance and other properties of such non-trivial methods.
Based on a well-known association between random walks and resistor networks, and building on a recently pointed-out connection with peer-to-peer networks, we tie-in a set of diverse techniques and metrics of both realms in a unifying framework. Furthermore, we present a basic set of tools to facilitate the analysis of overlay properties and the reasoning about algorithms for peer-to-peer networks. One of the key features of this framework is that it enables us to measure and contrast the local and global impact of algorithmic decisions in peer-to-peer networks. We provide example experimental studies that furthermore demonstrate its capabilities in the overlay network context.
KeywordsRandom Walk Fault Tolerance Degree Node Weighted Graph Overlay Network
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- 3.Ata, S., Murata, M., Gotoh, Y.: Replication methods for enhancing search performance in peer-to-peer services on power-law logical networks. In: Performance and Control of Next-Generation Communications Networks. SPIE, vol. 5244, pp. 76–85 (2003)Google Scholar
- 4.Gkantsidis, C., Mihail, M., Saberi, A.: Random walks in peer-to-peer networks. In: Proc. of 23rd Annual Joint Conf. of the IEEE Computer and Communications Societies (INFOCOM 2004), March 2004, vol. 1 (2004)Google Scholar
- 5.Sarshar, N., Boykin, P.O., Roychowdhury, V.P.: Percolation search in power law networks: making unstructured peer-to-peer networks scalable. In: Proc. of the 4th International Conf. on Peer-to-Peer Computing, pp. 2–9 (2004)Google Scholar
- 9.Voulgaris, S., Kermarrec, A.M., Massoulie, L.: Exploiting semantic proximity in peer-to-peer content searching. In: Proc. of 10th IEEE International Workshop on Future Trends of Distributed Computing Systems (FTDCS 2004), pp. 238–243 (2004)Google Scholar
- 13.Sohier, D., Bui, A.: Hitting times computation for theoretically studying peer-to-peer distributed systems. In: Proc. of the 18th International Parallel and Distributed Processing Symposium (2004)Google Scholar
- 15.Lv, Q., Cao, P., Cohen, E., Li, K., Shenker, S.: Search and replication in unstructured peer-to-peer networks. In: Proc. of the 16th International Conf. on Supercomputing (ICS 2002), pp. 84–95. ACM Press, New York (2002)Google Scholar
- 19.Chung, F.: Spectral Graph Theory. CBMS Regional Conf. Series in Mathematics, vol. 92. AMS (1997)Google Scholar
- 20.Doyle, P.G., Snell, L.J.: Random Walks and Electrical Networks. Mathematical Association of America (December 1984)Google Scholar
- 21.Chandra, A.K., Raghavan, P., Ruzzo, W.L., Smolensky, R.: The electrical resistance of a graph captures its commute and cover times. In: Proc. of the 21st Annual ACM Symposium on Theory of Computing (STOC 1989), pp. 574–586. ACM Press, New York (1989)Google Scholar
- 22.Alexander, C., Sadiku, M.: Fundamentals of Electric Circuits. McGraw-Hill, New York (2006)Google Scholar
- 26.Georgiadis, G., Kirousis, L.: Lightweight centrality measures in networks under attack. In: Proc. of European Conf. on Complex Systems, ECCS (2005)Google Scholar
- 27.Madduri, K., Bader, D.A., Berry, J.W., Crobak, J.R., Hendrickson, B.A.: Multithreaded algorithms for processing massive graphs. In: Bader, D.A. (ed.) Petascale Computing: Algorithms and Applications. Chapman & Hall/CRC Computational Science Series, Boca Raton (2008)Google Scholar
- 30.NVIDIA Corporation nvidia.com/cuda: NVIDIA CUDA Programming Guide. 2.0b edn. (2008)Google Scholar