SIAM Journal on Computing
Simple Markov-chain algorithms for generating bipartite graphs and tournaments
Random Structures & Algorithms
Chord: A scalable peer-to-peer lookup service for internet applications
Proceedings of the 2001 conference on Applications, technologies, architectures, and protocols for computer communications
A scalable content-addressable network
Proceedings of the 2001 conference on Applications, technologies, architectures, and protocols for computer communications
Measuring and analyzing the characteristics of Napster and Gnutella hosts
Multimedia Systems
Peer-to-peer networks based on random transformations of connected regular undirected graphs
Proceedings of the seventeenth annual ACM symposium on Parallelism in algorithms and architectures
FOCS '06 Proceedings of the 47th Annual IEEE Symposium on Foundations of Computer Science
Sampling Regular Graphs and a Peer-to-Peer Network
Combinatorics, Probability and Computing
A randomized algorithm for the joining protocol in dynamic distributed networks
Theoretical Computer Science
Building low-diameter peer-to-peer networks
IEEE Journal on Selected Areas in Communications
SBP'11 Proceedings of the 4th international conference on Social computing, behavioral-cultural modeling and prediction
Research note: On the uniformity of peer sampling based on view shuffling
Journal of Parallel and Distributed Computing
Physical expander in virtual tree overlay
DISC'11 Proceedings of the 25th international conference on Distributed computing
Correctness of Gossip-Based Membership under Message Loss
SIAM Journal on Computing
PODC '12 Proceedings of the 2012 ACM symposium on Principles of distributed computing
| Hi-index | 0.00 |
We define a network that relies on its protocol's emergent behaviour to maintain the useful properties of a random regular topology. It does this by spontaneously performing flips in an effort to randomise [15], allowing it to repair damage and to embed new peers without over-complicated joining schema. The main theoretical result of this paper is informed by the need to show that flips randomise the network quickly enough. Formally, we show that performing random flip operations on a regular graph of size n will rapidly sample from all such graphs almost uniformly at random (i.e. with error ε). Here, "rapidly" means in time polynomial in n and log ε−1. This is done by extending a similar result for random switches, obtained in [3], using a two-stage direct canonical path construction. The directness of our approach allows for a much tighter bound than obtained in previous work.