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Record W2245124102 · doi:10.1109/lcn.2015.7366292

Reliable surveillance in ring deployed Wireless Sensor Networks

2015· article· en· W2245124102 on OpenAlexaff
Mohammed Elmorsy, Ehab S. Elmallah

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicEnergy Efficient Wireless Sensor Networks
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsWireless sensor networkComputer scienceComputer networkIntrusion detection systemReliability (semiconductor)Key distribution in wireless sensor networksNode (physics)Process (computing)Wireless networkDistributed computingWirelessComputer securityEngineeringTelecommunications

Abstract

fetched live from OpenAlex

A common configuration used in area surveillance occurs when an area of interest is protected by deploying a number of concentric rings of sensor nodes around the area. When operating in a harsh environment, the nodes of the deployed Wireless Sensor Network (WSN) become subject to random failure. Consequently, the network becomes vulnerable to undetected unauthorized traversals to the area of interest. In this paper, we formulate a network wide reliability problem that quantifies the likelihood that the network continues to provide joint intrusion detection and reporting to a sink node at the center of the network. The algorithm uses a dynamic programming approach that strives to process many of the operating states of network while running efficiently. Our obtained numerical results illustrates the use of the algorithm as a network design tool.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.019
GPT teacher head0.227
Teacher spread0.208 · 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 source (direct Gemma or distilled Codex), 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

Citations1
Published2015
Admission routes1
Has abstractyes

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