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Record W1606207121 · doi:10.2478/v10248-012-0014-2

Energy Efficient Routing for Multi Hop Ad Hoc Networks with Multiple Access and Adaptive Modulation to Maximise Throughput

2012· article· en· W1606207121 on OpenAlex
Danish Khan, Peter Ball, Geoff Childs

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

VenueImage Processing & Communications · 2012
Typearticle
Languageen
FieldComputer Science
TopicMobile Ad Hoc Networks
Canadian institutionsHumber Polytechnic
Fundersnot available
KeywordsComputer scienceComputer networkThroughputEnergy consumptionWireless ad hoc networkNode (physics)WirelessLink adaptationTelecommunicationsFadingChannel (broadcasting)Electrical engineeringEngineering

Abstract

fetched live from OpenAlex

Abstract Wireless ad hoc networks are frequently deployed in strategic applications that require the use of battery powered nodes. A key requirement for these networks is to maximize the time span when all nodes have sufficient battery charge to participate in communication with other nodes. To meet this requirement, this paper describes a routing strategy that seeks to find the best balance between minimizing the power consumption and evenly using all nodes within the network to avoid early exhaustion of individual nodes. The proposed routing scheme is compared to reported schemes using minimum power routing and the results show that the proposed scheme gives a longer time until the first node’s battery energy is depleted with a lower network power consumption than schemes using just energy minimization. Multiple access techniques are discussed and a cost-effective scheme based on available wireless LAN channels and space division multiplexing is proposed. Each path can use one, two or three time slots according to the number of hops in the path. Adaptive modulation is used where the link power budget is sufficient to maintain the throughput per unit time regardless of the number of hops in the path. Simulation results show that the throughput can be significantly improved using adaptive modulation with a small reduction in the time until the first node’s battery energy is depleted.

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: Methods · Consensus signal: none
Teacher disagreement score0.888
Threshold uncertainty score0.878

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 communication0.0010.002
Open science0.0020.001
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 head0.062
GPT teacher head0.323
Teacher spread0.261 · 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