The DOI matches its Crossref record; 42 of the 42 references it cites were found in a registry or an index.
Gossip algorithms: design, analysis and applications
Abstract
Motivated by applications to sensor, peer-to-peer and ad hoc networks, we study distributed asynchronous algorithms, also known as gossip algorithms, for computation and information exchange in an arbitrarily connected network of nodes. Nodes in such networks operate under limited computational, communication and energy resources. These constraints naturally give rise to "gossip" algorithms: schemes which distribute the computational burden and in which a node communicates with a randomly chosen neighbor. We analyze the averaging problem under the gossip constraint for arbitrary network, and find that the averaging time of a gossip algorithm depends on the second largest eigenvalue of a doubly stochastic matrix characterizing the algorithm. Using recent results of Boyd, Diaconis and Xiao (2003), we show that minimizing this quantity to design the fastest averaging algorithm on the network is a semi-definite program (SDP). In general, SDPs cannot be solved distributedly; however, exploiting problem structure, we propose a subgradient method that distributedly solves the optimization problem over the network. The relation of averaging time to the second largest eigenvalue naturally relates it to the mixing time of a random walk with transition probabilities that are derived from the gossip algorithm. We use this connection to study the performance of gossip algorithm on two popular networks: wireless sensor networks, which are modeled as geometric random graphs, and the Internet graph under the so-called preferential connectivity model.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Boyd, S., & Vandenberghe, L. (2004) · doi:10.1017/cbo9780511804441 · Cited by 56,601
Self-citationConsensus Problems in Networks of Agents With Switching Topology and Time-Delays
Olfati-Saber, R., & Murray, R. M. (2004) · IEEE Transactions on Automatic Control · doi:10.1109/tac.2004.834113 · Cited by 12,788
Optimization and Nonsmooth Analysis
Clarke, F. H. (1990) · Society for Industrial and Applied Mathematics eBooks · doi:10.1137/1.9781611971309 · Cited by 10,264
Chord: A scalable peer-to-peer lookup service for internet applications
Stoica, I., Morris, R., Karger, D., Kaashoek, M. F., & Balakrishnan, H. (2001) · Proceedings of the 2001 conference on Applications, technologies, architectures, and protocols for computer communications · doi:10.1145/383059.383071 · Cited by 9,623
Coordination of groups of mobile autonomous agents using nearest neighbor rules
Jadbabaie, A., Lin, J., & Morse, A. S. (2003) · IEEE Transactions on Automatic Control · doi:10.1109/tac.2003.812781 · Cited by 8,339
The capacity of wireless networks
Gupta, P., & Kumar, P. R. (2000) · IEEE Transactions on Information Theory · doi:10.1109/18.825799 · Cited by 8,292
A scalable content-addressable network
Ratnasamy, S., Francis, P., Handley, M., Karp, R., & Shenker, S. (2001) · Proceedings of the 2001 conference on Applications, technologies, architectures, and protocols for computer communications · doi:10.1145/383059.383072 · Cited by 6,372
Large Deviations Techniques and Applications
Schmock, U., Dembo, A., & Zeitouni, O. (2000) · Journal of the American Statistical Association · doi:10.2307/2669805 · Cited by 3,524
TAG: a Tiny AGgregation service for ad-hoc sensor networks
Madden, S., Franklin, M. J., Hellerstein, J. M., & Hong, W. (2002) · ACM SIGOPS Operating Systems Review · doi:10.1145/844128.844142 · Cited by 2,719
Fast linear iterations for distributed averaging
Xiao, L., & Boyd, S. (2004) · Systems & Control Letters · doi:10.1016/j.sysconle.2004.02.022 · Cited by 2,706
Self-citation
Cited by
Consensus and Cooperation in Networked Multi-Agent Systems
Olfati-Saber, R., Fax, J. A., & Murray, R. M. (2007) · Proceedings of the IEEE · doi:10.1109/jproc.2006.887293 · Cited by 10,522
Distributed Subgradient Methods for Multi-Agent Optimization
Nedic, A., & Ozdaglar, A. (2009) · IEEE Transactions on Automatic Control · doi:10.1109/tac.2008.2009515 · Cited by 3,719
Vicsek, T., & Zafeiris, A. (2012) · Physics Reports · doi:10.1016/j.physrep.2012.03.004 · Cited by 2,923
Boyd, S., Ghosh, A., Prabhakar, B., & Shah, D. (2006) · IEEE Transactions on Information Theory · doi:10.1109/tit.2006.874516 · Cited by 2,439
Self-citationConstrained Consensus and Optimization in Multi-Agent Networks
Nedic, A., Ozdaglar, A., & Parrilo, P. A. (2010) · IEEE Transactions on Automatic Control · doi:10.1109/tac.2010.2041686 · Cited by 2,086
Metadata
- Authors
- Boyd, S., Ghosh, A., Prabbakar, B., & Shah, D.
- Venue
- Proceedings IEEE 24th Annual Joint Conference of the IEEE Computer and Communications Societies.
- Publisher
- IEEE
- Published
- 2005-08-24
- Volume
- 3
- Pages
- 1653-1664
- OpenAlex
- W2101517602
- Cited by
- 558
- References
- 42
- FWCI
- 30.79
- Type
- conference paper
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Gossip algorithms: design, analysis and applications. https://app.cochat.ai/papers/10.1109/infcom.2005.1498447
- The paper
- Boyd, S., Ghosh, A., Prabbakar, B., & Shah, D. (2005). Gossip algorithms: design, analysis and applications. Proceedings IEEE 24th Annual Joint Conference of the IEEE Computer and Communications Societies. https://doi.org/10.1109/infcom.2005.1498447
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
