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Record W2122642220 · doi:10.1109/icc.2008.429

A Utility-Based Incentive Scheme for P2P File Sharing in Mobile Ad Hoc Networks

2008· article· en· W2122642220 on OpenAlexaff
Afzal Mawji, Hossam S. Hassanein

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicMobile Ad Hoc Networks
Canadian institutionsQueen's University
Fundersnot available
KeywordsComputer scienceFile sharingScheme (mathematics)Mobile ad hoc networkIncentiveComputer networkFile transferWireless ad hoc networkDownloadFocus (optics)Peer-to-peerNetwork topologyDistributed computingTransfer (computing)Operating systemThe InternetMicroeconomicsWireless

Abstract

fetched live from OpenAlex

A synergy exists between MANETs and P2P networks since both are decentralized and have dynamic topologies. This paper presents a utility-based incentive scheme for P2P file sharing over MANETs, designed to encourage users to contribute to the network by sharing files. The scheme combines a virtual pricing mechanism with file transfer delay estimation and allows users to choose the best peer to download from based on their preference for price vs. delay. Users can choose to lower the delay experienced or focus on obtaining files for the lowest price. Simulation results show that the utility-based scheme does a much better job of promoting sharing of files by users in comparison to an unpriced and a fixed price scheme, the delay per downloaded file tends to be lower, and the MANET has a greater network lifetime.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.816
Threshold uncertainty score0.865

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.024
GPT teacher head0.251
Teacher spread0.227 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreMethods

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations11
Published2008
Admission routes1
Has abstractyes

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