Novel Energy-Efficient Opportunistic Routing Protocol for Marine Wireless Sensor Networks Based on Compressed Sensing and Power Control

• Published in: Journal of Ocean University of China 2022-12, Vol.21 (6), p.1504-1516
• Main Authors: Xian, Jiangfeng, Wu, Huafeng, Mei, Xiaojun, Zhang, Yuanyuan, Chen, Xinqiang, Zhang, Qiannan, Liang, Linian
• Format: Article
• Language: English
• Subjects: Adaptive control; Algorithms; Communication; Earth and Environmental Science; Earth Sciences; Energy; Energy consumption; Energy efficiency; Mathematical models; Meteorology; Network topologies; Nodes; Oceanography; Power control; Protocol; Routing (telecommunications); Sensors; Topology; Wireless networks; Wireless sensor networks
• ISSN: 1672-5182; 1993-5021; 1672-5174
• DOI: 10.1007/s11802-022-5128-6

In marine wireless sensor networks (MWSNs), an appropriate routing protocol is the key to the collaborative collection and efficient transmission of massive data. However, designing an appropriate routing protocol under the condition of sparse marine node deployment, highly dynamic network topology, and limited node energy is complicated. Moreover, the absence of continuous end-to-end connection introduces further difficulties in the design of routing protocols. In this case, we present a novel energy-efficient opportunistic routing (Novel Energy-Efficient Opportunistic Routing, NEOR) protocol for MWSNs that is based on compressed sensing and power control. First, a lightweight time-series prediction method-weighted moving average method is proposed to predict the packet advancement value such that the number of location information that is exchanged among a node and its neighbor nodes can be minimized. Second, an adaptive power control mechanism is presented to determine the optimal transmitting power and candidate node-set on the basis of node mobility, packet advancement, communication link quality, and remaining node energy. Subsequently, a timer-based scheduling algorithm is utilized to coordinate packet forwarding to avoid packet conflict. Furthermore, we introduce the compressed sensing theory to compress perceptual data at source nodes and reconstruct the original data at sink nodes. Therefore, energy consumption in the MWSNs is greatly reduced due to the decrease in the amount of data perception and transmission. Numerical simulation experiments are carried out in a wide range of marine scenarios to verify the superiority of our approach over selected benchmark algorithms.