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Record W2091788990 · doi:10.1145/2069000.2069012

Towards end-to-end routing for periodic mobile objects

2011· article· en· W2091788990 on OpenAlexafffund
Zhiyu Wang, Mário A. Nascimento, Michael H. MacGregor

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicOpportunistic and Delay-Tolerant Networks
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsComputer scienceFlooding (psychology)Dijkstra's algorithmShortest path problemRouting (electronic design automation)Path (computing)Base stationComputer networkGraphDistributed computingDomain (mathematical analysis)Real-time computingTheoretical computer scienceMathematics

Abstract

fetched live from OpenAlex

Mobile objects can be equipped with hardware enabling them to collect data, as well as answer queries remotely and in real-time. For the latter, one needs to be able to effectively route queries from a base station to the queried object in an efficient way, i.e., with minimum energy-cost or minimum delay. A complicating factor is that in many domains the mobile objects may not form a single connected component at all times. In this paper we take advantage of periodically repeating movements to establish encounter patterns, where an encounter is defined as a time-period long enough so that sensors can communicate with each other. Possessing such encounter patterns, we show how to model the query routing problem as a shortest path problem in a graph with domain-oriented constraints, and we also present polynomial time algorithms to find the guaranteed minimal delay and minimal energy routes. Furthermore, our experiments show that the minimal energy routes found by our algorithm have a cost of less than 1% of the cost obtained when using a flooding-based protocol.

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 score0.959
Threshold uncertainty score0.524

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 head0.044
GPT teacher head0.257
Teacher spread0.213 · 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

Citations2
Published2011
Admission routes2
Has abstractyes

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