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Record W2116202290 · doi:10.1109/lcn.2003.1243212

Energy aware routing protocol for mobile and wireless ad hoc networks

2004· article· en· W2116202290 on OpenAlexaff
Azzedine Boukerche, H. Owens

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicMobile Ad Hoc Networks
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsComputer networkComputer scienceMobile ad hoc networkOptimized Link State Routing ProtocolRouting protocolNetwork packetWireless Routing ProtocolWireless ad hoc networkDynamic Source RoutingEnergy consumptionAd hoc wireless distribution serviceDistributed computingThroughputWirelessTelecommunicationsEngineering

Abstract

fetched live from OpenAlex

MANET has resource limitations due to the nature of the network. Limitations are due to dynamic topology, memory and bandwidth constraints, and finite energy supply. To improve the QoS of the mobile client, we have made modifications to both DSR and TORA algorithms to make them energy aware ad hoc routing protocols. Our algorithms forward the route request packets based on the distance between the nodes, the energy level of the sending node and the receiving node. Our algorithms decrease network delay, increase network throughput and increase the number of data packets received at the destination while decreasing the per packet energy consumption by 20%, thereby increasing the network's life span.

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 score0.913
Threshold uncertainty score0.660

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 communication0.0000.000
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 head0.013
GPT teacher head0.264
Teacher spread0.251 · 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

Citations9
Published2004
Admission routes1
Has abstractyes

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