Increasing Energy Harvesting Rates for Underwater Wireless Sensor Networks Using Stochastic Network Calculus

Underwater Wireless Sensor Networks (UWSNs) enable real-time marine ecosystem monitoring but are constrained by limited energy availability, harsh underwater communication conditions, and high deployment costs. Although energy harvesting from water currents, vibrations, and ambient sources offers a sustainable solution, its efficiency is highly affected by dynamic underwater environments, and existing routing protocols such as Depth-Based Routing (DBR) do not explicitly support energy-harvesting awareness or dependable underwater Internet services. This paper proposes an enhanced DBR routing model that integrates energy-harvesting mechanisms with stochastic worst-case performance guarantees using a Stochastic Network Calculus (SNC)–based analytical framework. The proposed model evaluates end-to-end delay, energy utilization, routing stability, and network resilience under uncertain harvesting and communication conditions. Simulation results demonstrate that the enhanced DBR improves energy harvesting efficiency by approximately 30–35%, extends network lifetime by up to 40%, increases packet delivery ratio by 18–22%, and reduces end-to-end delay variability by around 25% compared to conventional DBR. These improvements enable sustained node operation, enhanced reliability, and more secure underwater Internet connectivity, confirming the suitability of the proposed approach for long-term and dependable UWSN deployment.