Energy-Efficient Data Transmission Strategies in Static Wireless Sensor Networks for Prolonged Network Lifetime

Abstract

Energy efficiency is a critical challenge in wireless sensor networks (WSNs), as sensor nodes are typically constrained by limited battery resources. Optimizing energy consumption through efficient transmission strategies is essential for prolonging network lifetime while maintaining reliable data delivery.  This paper presents a comprehensive analysis of energy-efficient data transmission strategies in static wireless sensor networks (WSNs) with the primary goal of extending overall network lifetime. We develop a novel multi-tier optimization framework that simultaneously addresses routing protocol efficiency, transmission power control, sleep scheduling mechanisms, and data aggregation techniques. Our mathematical model introduces a generalized energy consumption function that characterizes the complex interrelationships between transmission distance, packet size, node density, and environmental factors. Through extensive simulations on networks ranging from 100 to 10,000 nodes, we demonstrate that our hybrid approach achieves 37-42\% improvement in network lifetime compared to conventional methods. The proposed adaptive transmission power control algorithm dynamically adjusts node communication ranges based on residual energy levels and network topology, resulting in more balanced energy depletion across the network. Furthermore, our time-synchronized sleep scheduling protocol, working in conjunction with topology-aware clustering, reduces energy consumption by up to 53\% while maintaining packet delivery ratios above 98\%. These findings provide significant insights into the fundamental energy-efficiency trade-offs in WSNs and establish a theoretical upper bound on achievable network lifetime under practical constraints.