Evidence map›Paper›PMID 42817344›Full record

ArticleSensors (Basel, Switzerland)2026

SMA-WSN: Failure-Aware Slime-Mold-Inspired Clustering and Per-Hop Versus End-to-End Delivery Analysis in Agricultural Wireless Sensor Networks.

Messaoud Belloula, Souheila Bouam, Lyamine Guezouli, Djallel Eddine Boubiche, Homero Toral-Cruz, Rafael Sanchez-Lara, Rafael Martínez-Peláez, David Ernesto Troncoso Romero

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2026. 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

8 authors.

Messaoud BelloulaLAMIE (Laboratoire d'Applications des Mathématiques à l'Informatique et à l'Électronique), Department of Computer Sciences, University Batna 2, Batna 05000, Algeria.ORCID 0009-0001-5623-4610
Souheila BouamLAMIE (Laboratoire d'Applications des Mathématiques à l'Informatique et à l'Électronique), Department of Computer Sciences, University Batna 2, Batna 05000, Algeria.ORCID 0000-0002-2970-9625
Lyamine GuezouliLEREESI (Laboratory of Renewable Energy, Energy Efficiency and Smart Systems) Laboratory, HNS-RE2SD (Higher National School of Renewable Energies, Environment and Sustainable Development), Batna 05000, Algeria.ORCID 0000-0002-7406-7633
Djallel Eddine BoubicheLEREESI (Laboratory of Renewable Energy, Energy Efficiency and Smart Systems) Laboratory, HNS-RE2SD (Higher National School of Renewable Energies, Environment and Sustainable Development), Batna 05000, Algeria.ORCID 0000-0002-1566-3005
Homero Toral-CruzDepartamento de Ingeniería y Tecnología, Universidad Autónoma del Estado de Quintana Roo, Chetumal 77019, Mexico.ORCID 0000-0002-4421-3775
Rafael Sanchez-LaraFacultad de Ingeniería y Arquitectura, Universidad Autónoma del Carmen, Ciudad del Carmen 24180, Mexico.
Rafael Martínez-PeláezUnidad Académica de Computación, Universidad Politécnica de Sinaloa, Mazatlán 82199, Mexico.ORCID 0000-0003-2188-9892
David Ernesto Troncoso RomeroDivisión de Ciencias Multidisciplinarias Cancún, Universidad Autónoma del Estado de Quintana Roo, Cancún 77519, Mexico.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Wireless sensor networks in agricultural fields face abrupt node failures from environmental stress and physical damage, yet most clustering protocols assume fault-free operation. This paper proposes SMA-WSN, a failure-aware clustering protocol inspired by the Slime Mold Algorithm, selecting cluster heads via a tri-objective fitness that combines residual energy, base-station proximity, and local coverage. Evaluated in NS-3.47 against 11 protocols over six agricultural topology archetypes-spatial node-layout patterns derived from Algerian field geometries and densities, not biophysical canopy or soil-moisture propagation models-and five failure rates (18,000 runs, 50 seeds), SMA-WSN achieves the highest per-hop delivery ratio at every failure rate and ranks first overall on that metric, with its largest margins on the heterogeneous, oasis, and sparse-Saharan terrains (T4-T6). We also report an end-to-end delivery ratio, counting a datum only when it reaches the base station: under that stricter definition, all 12 protocols change rank, and SMA-WSN places seventh. We report both and treat the divergence between them as a result in its own right. SMA-WSN achieves the highest per-hop PDR while remaining statistically tied with the best protocols in energy fairness (Jain index 0.922, within one confidence half-width of the leaders GWO-LEACH, PSO-LEACH, and FGO-QL). An ablation over the three fitness terms and their weights shows this advantage is robust to objective weighting and arises from the SMA selection dynamics rather than any single fitness term: no term, including coverage, is individually decisive, so the advantage does not depend on a finely tuned weighting. Disabling the stochastic wrap phase, by contrast, costs 11.4 percentage points of per-hop PDR, identifying it as the mechanism actually responsible for the gain. On First Node Death under failure, SMA-WSN is mid-field rather than dominant; we report this honestly and discuss it as an open question for follow-up work distinguishing energy-exhaustion deaths from abrupt hardware failures.

Indexed as

Algeriabio-inspired clusteringfailure-rate sensitivityfault resiliencenode failureNS-3packet-delivery ratioprecision agricultureslime mold algorithmwireless sensor networks

Identifiers

PMID42817344
PMCPMC13611697

What OpenQuestion holds

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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.