Adaptive Data Collection and Transmission Protocols to Enhance Energy Conservation in Wireless Sensor Networks Deployed in Harsh Environments

Abstract

Energy-efficient communication is crucial for wireless sensor networks (WSNs) deployed in extreme environments, where unpredictable disturbances and resource constraints pose significant challenges. Optimizing data collection and transmission strategies in such conditions is essential to ensure long-term network operation and reliable data delivery.  This paper proposes an innovative framework for adaptive data collection and transmission protocols designed to optimize energy usage in WSNs operating in harsh environmental conditions. The study develops a rigorous mathematical model that incorporates continuous time-space representations, stochastic differential equations, and variational optimization techniques to formulate energy-efficient and disturbance-resilient transmission schedules and data aggregation strategies. A system of coupled differential equations is derived to characterize sensor node energy depletion, nonlinear wireless signal propagation, and interference effects arising from environmental fluctuations. The proposed framework leverages iterative optimization methods, such as gradient descent and Newton-Raphson algorithms, to dynamically regulate transmission power and compression parameters in real time. Simulation results demonstrate that the adaptive protocols significantly enhance network longevity while preserving high data fidelity, outperforming traditional fixed-parameter strategies in severe operational scenarios. By integrating advanced theoretical principles with practical algorithmic solutions, this approach offers new perspectives on managing energy constraints in remote sensing applications. Furthermore, the incorporation of predictive time-series analysis strengthens the network's ability to anticipate energy depletion, ensuring sustained and reliable data transmission. This work establishes a robust foundation for the development of energy-aware communication systems, paving the way for scalable and resilient sensor network architectures in challenging environments.