A Novel Energy Efficient Approach for Reliable Path Recovery and Fault Tolerant Communication in Dynamic Wireless Sensor Networks

Abstract

Wireless Sensor Networks (WSNs) have become an integral part of applications such as environmental monitoring, industrial automation, healthcare systems, and military surveillance due to their ability to provide efficient and reliable data collection. In these networks, recovering the routing path of individual packets is critical for network monitoring, fault diagnosis, intrusion detection, delay analysis, and topology management. However, the dynamic nature of wireless sensor networks, characterized by frequent topology changes, unreliable wireless links, and limited energy and computational resources, makes accurate packet path recovery a complex and challenging task. This paper proposes an enhanced Compressive Sensing-based Path Recovery (CSPR) framework for dynamic wireless sensor networks. The proposed framework models the network as a sparse path representation space in which every routing path is represented by a sparse vector. Since only a small subset of sensor nodes participates in forwarding each packet, compressive sensing enables efficient recovery of routing paths from a limited number of packet observations while maintaining low communication overhead. The CSPR framework integrates Bloom filters with encoded measurement vectors to compactly embed routing information within packet headers without introducing significant transmission overhead. In contrast to conventional path recovery techniques that depend on stable routing structures and inter-packet correlations, the proposed framework effectively adapts to topology variations, packet losses, and unreliable wireless communication links. Furthermore, optimization strategies, including representation space reduction and heuristic path scanning, are incorporated to improve recovery efficiency and accuracy while reducing computational complexity. Experimental analysis and simulation results demonstrate that the proposed framework achieves high path recovery accuracy with minimal packet overhead and significantly outperforms existing approaches in dynamic network scenarios. The results confirm that the proposed CSPR framework provides a scalable, reliable, and energy-efficient solution for per-packet path recovery in modern wireless sensor networks.