A Potential-Game-Based Self-Organizing Underwater Sensing Network for Energy-Efficient and Reliable Measurement Data Acquisition

Abstract

Long-term underwater measurement tasks require continuous and reliable sensing-data acquisition, yet underwater wireless sensor networks (UWSNs) are constrained by limited node energy, uneven cluster distribution, unstable acoustic links, and energy-hole effects near the sink. These limitations may cause premature node failure and degradation of measurement-data delivery. To address these issues, this paper proposes a Potential Game-based Self-Organizing Clustering and Adaptive Routing algorithm (PG-ORG) for three-dimensional UWSNs. Each node first makes a binary candidate cluster-head (CH) participation decision through a local potential game considering residual energy, distance, link quality, and node density. After convergence, non-candidate nodes associate with the resulting candidate CHs to form the final clusters. A multi-metric voting mechanism and energy-triggered CH rotation are further employed to balance CH workload, while adaptive direct/multi-hop routing reduces long-distance transmission cost and relay hotspots. PG-ORG relies on locally exchangeable state information and avoids per-round global optimization. Simulation results demonstrate that PG-ORG improves network lifetime, energy balance, throughput, and measurement-data delivery reliability compared with the benchmark protocols. Additional experiments under meandering-current and tidal-current mobility further confirm the robustness of PG-ORG under time-varying underwater topologies.