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Record W2116900310 · doi:10.1109/msn.2010.31

Mobility-Based Strategies for Energy Restoration in Wireless Sensor Networks

2010· article· en· W2116900310 on OpenAlexaff
Elio Velazquez, Nicola Santoro

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicEnergy Efficient Wireless Sensor Networks
Canadian institutionsCarleton University
Fundersnot available
KeywordsCompassWireless sensor networkComputer scienceComputer networkNetwork topologyRedistribution (election)Efficient energy useDistributed computingEngineeringElectrical engineering

Abstract

fetched live from OpenAlex

Energy management has become one of the main hurdles in the quest for autonomous and reliable Wireless Sensor Networks (WSN). This paper examines the emerging problem of increasing network availability by recharging, replacing or redeploying depleted sensors with the help of mobile entities. When mobility becomes a sensor's attribute and service stations are static, we propose passive vs. pro-active approaches to energy redistribution and restoration. In particular, for pro-active approaches, we study the mobility strategies and underlying topologies that guarantee a successful sensor recharge. The experimental results so far show that taking our novel pro-active approach to energy redistribution and network fatigue outperforms passive strategies. The proposed closest-first swapping-based mobility strategy provides the best overall performance among all the pro-active approaches studied and the proposed Compass Directed Unit Graph provides an efficient and flexible underlying topology to achieve energy equilibrium.

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)0.001
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.809
Threshold uncertainty score0.782

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.011
GPT teacher head0.236
Teacher spread0.225 · 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
GenreEmpirical

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
Published2010
Admission routes1
Has abstractyes

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