Journal of the ACM (JACM) - The MIT Press scientific computation series
Templates for the solution of algebraic eigenvalue problems: a practical guide
Templates for the solution of algebraic eigenvalue problems: a practical guide
Journal of Computational and Applied Mathematics - Special issue on numerical analysis 2000 Vol. III: linear algebra
The Eigentrust algorithm for reputation management in P2P networks
WWW '03 Proceedings of the 12th international conference on World Wide Web
Distributed Pagerank for P2P Systems
HPDC '03 Proceedings of the 12th IEEE International Symposium on High Performance Distributed Computing
Statistical mechanics of complex networks
Statistical mechanics of complex networks
Gossip-Based Computation of Aggregate Information
FOCS '03 Proceedings of the 44th Annual IEEE Symposium on Foundations of Computer Science
Vivaldi: a decentralized network coordinate system
Proceedings of the 2004 conference on Applications, technologies, architectures, and protocols for computer communications
The peer sampling service: experimental evaluation of unstructured gossip-based implementations
Proceedings of the 5th ACM/IFIP/USENIX international conference on Middleware
Gossip-based aggregation in large dynamic networks
ACM Transactions on Computer Systems (TOCS)
Efficient and decentralized PageRank approximation in a peer-to-peer web search network
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
COCOON'03 Proceedings of the 9th annual international conference on Computing and combinatorics
Peer-to-peer multi-class boosting
Euro-Par'12 Proceedings of the 18th international conference on Parallel Processing
| Hi-index | 0.00 |
The dominant eigenvector of matrices defined by weighted links in overlay networks plays an important role in many peer-to-peer applications. Examples include trust management, importance ranking to support search, and virtual coordinate systems to facilitate managing network proximity. Robust and efficient asynchronous distributed algorithms are known only for the case when the dominant eigenvalue is exactly one. We present a fully distributed algorithm for a more general case: non-negative square matrices that have an arbitrary dominant eigenvalue. The basic idea is that we apply a gossip-based aggregation protocol coupled with an asynchronous iteration algorithm, where the gossip component controls the iteration component. The norm of the resulting vector is an unknown finite constant by default; however, it can optionally be set to any desired constant using a third gossip control component. Through extensive simulation results on artificially generated overlay networks and real web traces we demonstrate the correctness, the performance and the fault tolerance of the protocol.