MétaCan
Menu
Back to cohort
Record W2162413306 · doi:10.1109/mwc.2008.4599216

MAC layer misbehavior in wireless networks: challenges and solutions

2008· article· en· W2162413306 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueIEEE Wireless Communications · 2008
Typearticle
Languageen
FieldComputer Science
TopicWireless Networks and Protocols
Canadian institutionsConcordia University
Fundersnot available
KeywordsComputer networkComputer scienceWireless ad hoc networkNetwork allocation vectorLayer (electronics)Bandwidth (computing)Multiple Access with Collision Avoidance for WirelessWirelessProtocol (science)Link layerNetwork layerWireless networkApplication layerIEEE 802.11Routing protocolNetwork packetOptimized Link State Routing ProtocolTelecommunications

Abstract

fetched live from OpenAlex

IEEE 802.11 CSMA/CA has been widely deployed as the primary MAC protocol for ad hoc networks and wireless LANs. It was designed with the assumption that nodes would follow proper operation of the protocol. Nodes, however, may choose to deviate in order to either obtain an unfair share of the available bandwidth or disrupt the services of the network. Accordingly, a misbehavior rooted at the MAC layer can be classified as selfish or malicious behavior. This article surveys the research activities related to MAC layer misbehavior; based on the operating principles and the objective of misbehaving nodes, we classify MAC layer misbehavior and present descriptions for each solution. We conclude with a brief summary of the key ideas and a general direction for future work.

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.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.881
Threshold uncertainty score1.000

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 studies0.0010.000
Scholarly communication0.0000.001
Open science0.0020.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.124
GPT teacher head0.303
Teacher spread0.179 · 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