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Record W2115026050 · doi:10.1504/ijwmc.2013.053040

On routing protocols using mobile social networks

2013· article· en· W2115026050 on OpenAlex
Ahmed B. Altamimi, T. Aaron Gulliver

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

VenueInternational Journal of Wireless and Mobile Computing · 2013
Typearticle
Languageen
FieldComputer Science
TopicOpportunistic and Delay-Tolerant Networks
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsComputer scienceComputer networkRouting protocolWireless Routing ProtocolNode (physics)Link-state routing protocolDynamic Source RoutingDestination-Sequenced Distance Vector routingSoftware deploymentDistributed computingPolicy-based routingMobile social networkRouting (electronic design automation)Mobile computing

Abstract

fetched live from OpenAlex

A Mobile Social Network (MSN) is defined as a mobile network that uses social relationships to determine node communication. Many wireless networks including ad hoc networks do not reflect a real world deployment because of routing implementation difficulties. However, with the enormous use of Social Network Sites (SNSs) including Twitter and Facebook, MSNs can be exploited to make routing easier. Although there has been some research effort devoted to routing using these networks, the MSN routing protocols proposed in the literature suffer from either a low delivery ratio or high memory requirements. This paper presents a new routing protocol (status) for MSNs which has excellent performance in terms of delivery ratio and memory requirements. It employs the online status of a node to make forwarding decisions. Status has a low overhead ratio, low average delay and low computational complexity at the node level.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.953
Threshold uncertainty score0.542

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.022
GPT teacher head0.304
Teacher spread0.282 · 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