A novel strategic trajectory-based protocol for enhancing efficiency in wireless sensor networks

This research presents a comprehensive approach to enhance the efficiency and performance of Wireless Sensor Networks (WSNs) by addressing critical challenges, such as race conditions, reservation problems, and redundant data. A novel protocol combining Self-Adaptive Redundancy Elimination Clustering and Distributed Load Bandwidth Management is proposed to mitigate these challenges. The work intelligently extracts transmission hops and any-cast transmission features from diversity traffic information obtained through trace files, to eliminate nodes harboring redundant data. To optimize network organization, the number of clusters is dynamically adjusted according to the node density using the affinity propagation technique. Furthermore, load balancing is achieved by reallocating available bandwidth through bandwidth re-segmentation. The research also delves into the Proposed Network Infrastructure and Channel Coordination. The architecture encompasses cooperative clustering of nodes, strategic access point selection, data compression, and channel migration. By fostering collaboration among nodes within clusters, selecting access points judiciously, and employing efficient data compression techniques, the network overall efficiency is significantly improved. Channel migration strategies further bolster the network agility and responsiveness. The integration of Channel Sensing enriches the approach by collecting channel state information, enriched with spatial and temporal node information. This added insight empowers the network to make more informed decisions regarding channel allocation and coordination contributing to reduced interference and optimized data transmission. As a result of the work, the proposed methodology achieves remarkable results, including an average Packet Delivery Ratio of 99.1 % and an average reduction of packet loss by 4.3 % compared to existing studies. Additionally, the proposed protocol exhibits an average throughput improvement of 4.7 % and reduces average network delay to 52 milliseconds highlighting its significant contributions to the enhancement of WSN performance.