Evidence map›Paper›PMID 40640328›Full record

ArticleScientific reports2025

Enhancing the effectiveness of wireless sensor networks through consensus estimation and universal coverage.

Hua Tian

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

1 author.

Hua TianSchool of Intelligence & Electronic Engineering, Dalian Neusoft University of Information, Dalian, 116023, Liaoning, China. tianhuagzu@126.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Wireless sensor networks (WSNs) consist of numerous sensor nodes equipped with sensing, computing, and communication capabilities, where battery power is a critical limitation. Efficient energy management is vital to ensure sustained WSN performance. This study introduces a novel approach to enhance coverage and minimize energy consumption in WSNs. The method divides the network environment into distinct regions, activating only one node per region based on its residual energy and centrality, while other nodes enter a low-energy sleep mode to conserve power. Active nodes are periodically reselected through a duty cycle to distribute energy load and prevent premature node shutdowns. To address uncovered regions, a consensus estimation algorithm uses data from neighboring active nodes, weighted by their proximity, to estimate environmental data, ensuring continuous coverage. Additionally, multi-hop routing optimizes data transmission to the base station by reducing transmission distances, further enhancing energy efficiency. Simulation results across multiple scenarios demonstrate that this approach significantly reduces energy consumption and extends network lifetime compared to existing protocols, such as LEACH, LEACH-C, and ECRM, achieving approximately 60% and 20% improvements over LEACH and ECRM, respectively. This method effectively balances coverage and energy efficiency, making it a robust solution for WSN applications.

Indexed as

Consensus EstimationCoverageDuty cycleWireless sensor networksZoning

Identifiers

PMID40640328
PMCPMC12246112

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.