Evidence map›Paper›PMID 34770561›Full record

ArticleSensors (Basel, Switzerland)2021

Reliable Route Selection for Wireless Sensor Networks with Connection Failure Uncertainties.

Jianhua Lyu, Yiran Ren, Zeeshan Abbas, Baili Zhang

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Jianhua LyuSchool of Computer Science and Engineering, Southeast University, Nanjing 210096, China.ORCID 0000-0002-4961-1676
Yiran RenSchool of Computer Science and Engineering, Southeast University, Nanjing 210096, China.ORCID 0000-0002-4559-9155
Zeeshan AbbasSchool of Computer Science and Engineering, Southeast University, Nanjing 210096, China.
Baili ZhangSchool of Computer Science and Engineering, Southeast University, Nanjing 210096, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

For wireless sensor networks (WSN) with connection failure uncertainties, traditional minimum spanning trees are no longer a feasible option for selecting routes. Reliability should come first before cost since no one wants a network that cannot work most of the time. First, reliable route selection for WSNs with connection failure uncertainties is formulated by considering the top-k most reliable spanning trees (RST) from graphs with structural uncertainties. The reliable spanning trees are defined as a set of spanning trees with top reliabilities and limited tree weights based on the possible world model. Second, two tree-filtering algorithms are proposed: the k minimum spanning tree (KMST) based tree-filtering algorithm and the depth-first search (DFS) based tree-filtering algorithm. Tree-filtering strategy filters the candidate RSTs generated by tree enumeration with explicit weight thresholds and implicit reliability thresholds. Third, an innovative edge-filtering method is presented in which edge combinations that act as upper bounds for RST reliabilities are utilized to filter the RST candidates and to prune search spaces. Optimization strategies are also proposed for improving pruning capabilities further and for enhancing computations. Extensive experiments are conducted to show the effectiveness and efficiency of the proposed algorithms.

Indexed as

Computer Communication NetworksWireless TechnologyAlgorithmsReproducibility of ResultsUncertaintyconnection failure uncertaintyfilteringreliable spanning treeroute selectionwireless sensor networks

Identifiers

PMID34770561
PMCPMC8588549

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.