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Distributed Navigation Algorithms for Sensor Networks

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Chiranjeeb Buragohain, Divyakant Agrawal, Subhash Suri

Networking and Internet Architecture · Submitted 14 Dec 2005

abstract compiled · 2026-09-23 · no language-model review

The authors' main claim Using skeleton graphs we show that it is possible to find approximate safe paths with much lower communication cost.

how it is stated · asserted 0.59 read the record →

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arXiv IDcs/0512060 (version 1)
Pith IDVMWRPHRU, Pith's permanent record of this paper and its review
CitationChiranjeeb Buragohain, Divyakant Agrawal, Subhash Suri. "Distributed Navigation Algorithms for Sensor Networks." arXiv:cs/0512060 (2005). https://pith.science/paper/VMWRPHRU
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The compiled record

The paper's own sentences, arranged. Each label is drawn from a closed vocabulary; the number beside it is the probability the classifier gave that label. Numbers in the tables are the authors', checked by code. No sentence in this record was written by a model.

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Compiled by classifier-1.13-20260917 via OpenRouter, question bank abstract-p1-20260923, 2026-09-23: 1 request, 4,790 input tokens, $0.0002 reported.

What the abstract itself states, as probabilities: claims first 0.04 · states limitation 0.27 · human participants 0.07 · controlled comparison 0.44 · randomized assignment 0.01 · states quantitative result 0.14 · compares with prior results 0.90 · mentions code or data availability 0.02.

The abstract, sentence by sentence

arXiv listing abstract v1. Results and the main claim are underlined; .

We propose efficient distributed algorithms to aid navigation of a user through a geographic area covered by sensors. The sensors sense the level of danger at their locations and we use this information to find a safe path for the user through the sensor field. Traditional distributed navigation algorithms rely upon flooding the whole network with packets to find an optimal safe path. To reduce the communication expense, we introduce the concept of a skeleton graph which is a sparse subset of the true sensor network communication graph. Using skeleton graphs we show that it is possible to find approximate safe paths with much lower communication cost. We give tight theoretical guarantees on the quality of our approximation and by simulation, show the effectiveness of our algorithms in realistic sensor network situations.

background contribution method result interpretation main claim

What the classifier reports for each sentence. The number is the probability it gave the label.
#sentencerolethe authors' own workstates the main conclusionstrength
s0 We propose efficient distributed algorithms to aid navigation of a user through a geographic area covered by sensors. contribution 1.00 0.90 0.12 asserted 0.96
s1 The sensors sense the level of danger at their locations and we use this information to find a safe path for the user through the sensor field. method 0.59 0.76 0.07 asserted 1.00
s2 Traditional distributed navigation algorithms rely upon flooding the whole network with packets to find an optimal safe path. background 0.96 0.04 0.03 asserted 1.00
s3 To reduce the communication expense, we introduce the concept of a skeleton graph which is a sparse subset of the true sensor network communication graph. contribution 0.55 0.82 0.08 asserted 0.98
s4 Using skeleton graphs we show that it is possible to find approximate safe paths with much lower communication cost. result 0.81 0.95 0.60 asserted 0.59
s5 We give tight theoretical guarantees on the quality of our approximation and by simulation, show the effectiveness of our algorithms in realistic sensor network situations. result 0.54 0.96 0.62 asserted 1.00

What kind of paper the classifier reports this is: method or tool 1.00 · evidence from simulation or computation 0.81.

What was examined, and what was not

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  • full text
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  • references and citing sentences
  • relations to other papers
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  • P abstract
not run
  • S sections
  • T body sentences
  • C citations
  • R cross-paper relations

Every quoted sentence on this record is the authors'. Every label is from Pith's closed vocabulary, with the probability shown beside it. Every number in the measurements table is the authors', checked by code. Record as JSON

The paper
Original abstract

We propose efficient distributed algorithms to aid navigation of a user through a geographic area covered by sensors. The sensors sense the level of danger at their locations and we use this information to find a safe path for the user through the sensor field. Traditional distributed navigation algorithms rely upon flooding the whole network with packets to find an optimal safe path. To reduce the communication expense, we introduce the concept of a skeleton graph which is a sparse subset of the true sensor network communication graph. Using skeleton graphs we show that it is possible to find approximate safe paths with much lower communication cost. We give tight theoretical guarantees on the quality of our approximation and by simulation, show the effectiveness of our algorithms in realistic sensor network situations.

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