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Record W1774937627 · doi:10.1109/lcn.2004.135

Voilaˋ: delivering messages across partitioned ad-hoc networks

2005· article· en· W1774937627 on OpenAlexaff
Rahul Shah, N.C. Hutchinson, William Evans

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicMobile Ad Hoc Networks
Canadian institutionsUniversity of British Columbia
FundersDepartment of Science and Technology, Ministry of Science and Technology, India
KeywordsComputer networkComputer scienceNetwork packetWireless ad hoc networkMobile ad hoc networkPartition (number theory)Routing protocolNetwork partitionDistributed computingRouting (electronic design automation)WirelessWireless networkHost (biology)TelecommunicationsMathematics

Abstract

fetched live from OpenAlex

Many routing protocols have been developed to establish and maintain routes in mobile ad-hoc networks (MANETs). They try to address the unique challenges that MANETs present over traditional wired networks. Some of these challenges are: use of unreliable wireless medium for communication; frequent change in topology; lack of a central authority to arbitrate communication in the network. These protocols find a route to a destination, if such a route exists. However in the wireless medium, links are susceptible to frequent failures which can cause partitions in the network. Current routing protocols use a passive delivery approach for packets destined to a host in another partition. Packets destined to a disconnected host are dropped after some route repair attempts. The paper presents a novel protocol, Voila/spl grave/, that delivers messages across disconnected hosts. Voila/spl grave/ uses nodes moving between the source and destination partitions to act as carriers of messages. It uses a novel carrier select algorithm to select carrier nodes in the source partition.

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 score0.906
Threshold uncertainty score0.695

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 communication0.0000.001
Open science0.0010.001
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 head0.012
GPT teacher head0.253
Teacher spread0.241 · 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

Citations3
Published2005
Admission routes1
Has abstractyes

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