Hybrid compression-based routing strategies for enhanced energy efficiency in wireless sensor networks

Abstract Wireless Sensor Networks (WSNs) are essential in a wide range of applications, from environmental monitoring to industrial automation. However, the limited battery life of sensor nodes is a critical challenge, especially in large-scale deployments where frequent battery replacements are impractical. This study proposes a hybrid compression-based routing strategy to enhance energy efficiency in WSNs. Our approach combines Adaptive Lossless Data Compression (ALDC) with optimized routing protocols, explicitly leveraging Ant Colony Optimization (ACO) and Cuckoo Search (CS) to reduce data size before transmission and optimize the data forwarding paths. The results indicate that the proposed method significantly outperforms traditional routing strategies in terms of both energy consumption and network longevity. Specifically, our hybrid approach achieved a 40% reduction in energy usage, noticeable gains in data delivery ratio 32% and reduced packet loss, affirming its robustness and reliability compared to conventional methods, extending the network lifetime by approximately 25%. Furthermore, the compression ratio reached 78%, demonstrating the effectiveness of ALDC in minimizing data size without compromising data integrity. Network throughput also improved, with a reduction in path length by 84%, thus enhancing the reliability and responsiveness of the WSN. In conclusion, the hybrid compression-based routing strategy offers a promising solution for energy-efficient data transmission in WSNs, supporting prolonged network operations and ensuring reliable data delivery. This approach is particularly suitable for resource-constrained environments, where energy savings are paramount. Future work will refine the compression algorithm for dynamic data patterns and explore real-time adaptability in diverse WSN applications.