The DOI matches its Crossref record.
A local search mechanism for peer-to-peer networks
Abstract
One important problem in peer-to-peer (P2P) networks is searching and retrieving the correct information. However, existing searching mechanisms in pure peer-to-peer networks are inefficient due to the decentralized nature of such networks. We propose two mechanisms for information retrieval in pure peer-to-peer networks. The first, the modified Breadth-First Search (BFS) mechanism, is an extension of the current Gnuttela protocol, allows searching with keywords, and is designed to minimize the number of messages that are needed to search the network. The second, the Intelligent Search mechanism, uses the past behavior of the P2P network to further improve the scalability of the search procedure. In this algorithm, each peer autonomously decides which of its peers are most likely to answer a given query. The algorithm is entirely distributed, and therefore scales well with the size of the network. We implemented our mechanisms as middleware platforms. To show the advantages of our mechanisms we present experimental results using the middleware implementation.
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
Cited by
Survey of research towards robust peer-to-peer networks: Search methods
Risson, J., & Moors, T. (2006) · Computer Networks · doi:10.1016/j.comnet.2006.02.001 · Cited by 386
Energy Efficiency Dilemma: P2P-cloud vs. Datacenter
Sharifi, L., Rameshan, N., Freitag, F., & Veiga, L. (2014) · 2014 IEEE 6th International Conference on Cloud Computing Technology and Science · doi:10.1109/cloudcom.2014.137 · Cited by 20
Metadata
- Authors
- Kalogeraki, V., Gunopulos, D., & Zeinalipour-Yazti, D.
- Venue
- Proceedings of the eleventh international conference on Information and knowledge management
- Publisher
- ACM
- Published
- 2002-11-04
- Pages
- 300-307
- OpenAlex
- W2098125775
- Cited by
- 369
- References
- 0
- FWCI
- 10.01
- 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: A local search mechanism for peer-to-peer networks. https://app.cochat.ai/papers/10.1145/584792.584842
- The paper
- Kalogeraki, V., Gunopulos, D., & Zeinalipour-Yazti, D. (2002). A local search mechanism for peer-to-peer networks. Proceedings of the eleventh international conference on Information and knowledge management. https://doi.org/10.1145/584792.584842
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.