Choosing a Random Peer in Chord

Authors:
Valerie King;Scott Lewis;Jared Saia;Maxwell Young
Affiliations:
University of Victoria, Department of Computer Science, P.O. Box 3055, V8W 3P6, Victoria, BC, Canada;University of New Mexico, Department of Computer Science, P.O. Box 3055, 87131-1386, Albuquerque, NM, USA;University of New Mexico, Department of Computer Science, P.O. Box 3055, 87131-1386, Albuquerque, NM, USA;University of New Mexico, Department of Computer Science, P.O. Box 3055, 87131-1386, Albuquerque, NM, USA
Venue:
Algorithmica
Year:
2007

Citing 0
Cited 2

Distribution fairness in Internet-scale networks

ACM Transactions on Internet Technology (TOIT)
Optimal gossip-based aggregate computation

Proceedings of the twenty-second annual ACM symposium on Parallelism in algorithms and architectures

Quantified Score

Hi-index	0.00

Visualization

Abstract

We present two new algorithms, Arc Length and Peer Count, for choosing a peer uniformly at random from the set of all peers in Chord (Proceedings of the ACM SIGCOMM 2001 Technical Conference, 2001). We show analytically that, in expectation, both algorithms have latency O(log n) and send O(log n) messages. Moreover, we show empirically that the average latency and message cost of Arc Length is 10.01log n and that the average latency and message cost of Peer Count is 20.02log n. To the best of our knowledge, these two algorithms are the first fully distributed algorithms for choosing a peer uniformly at random from the set of all peers in a Distributed Hash Table (DHT). Our motivation for studying this problem is threefold: to enable data collection by statistically rigorous sampling methods; to provide support for randomized, distributed algorithms over peer-to-peer networks; and to support the creation and maintenance of random links, and thereby offer a simple means of improving fault-tolerance.