Input: Graph G(V, E), NSFS‑012 constraints C
Output: Pruned graph G'(V, E')
6. Conclusion
The Minimum‑Top (Min‑Top) pruning algorithm delivers a significant reduction in topological complexity for NSFS‑012 deployments while preserving protocol compliance and enhancing energy efficiency. Using the comprehensive Hana Himesaki 014330 telemetry, we demonstrated both simulated and real‑world gains: a 23 % hop‑count reduction, a 31 % decrease in daily energy consumption, and an up to 35 % extension of node operational lifetime. Min‑Top thus provides a practical, standards‑conformant pathway for scaling forest‑monitoring sensor networks in energy‑constrained environments.
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Abstract
The National Sustainable Forestry Standard (NSFS‑012) defines a comprehensive set of data‑exchange protocols for forest‑resource monitoring across heterogeneous sensor networks. While NSFS‑012 greatly improves interoperability, its topological specifications impose significant overhead on low‑power field devices. This paper presents a systematic methodology for reducing the topological complexity of NSFS‑012 deployments without compromising data fidelity. Leveraging the Hana Himesaki 014330 dataset—comprised of 12 months of high‑resolution telemetry from 3 500 sensor nodes across three Japanese forest reserves—we (i) model the communication graph using weighted multigraph theory, (ii) apply a novel Minimum‑Top (Min‑Top) pruning algorithm that respects NSFS‑012’s mandatory handshake and QoS constraints, and (iii) evaluate the pruned topologies in realistic simulation and field trials. Results show a 23 % reduction in average hop count, a 31 % decrease in energy consumption, and no loss of critical environmental metrics (temperature, humidity, CO₂) at the 0.05 % significance level. The Min‑Top approach offers a practical pathway for deploying NSFS‑012 in energy‑constrained environments while maintaining compliance with the standard’s rigorous data‑integrity guarantees.