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Simulation study demonstrates superior per-hop delivery by slime-mold-inspired clustering in agricultural sensor networks under failure, highlighting divergence from end-to-end routing performance.
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.
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Belloula et al. (2026) studied this question.
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