Energy-efficiency Technology In Underwater Wireless Sensor Networks And Its Applications For Marine Logistics Transportation

With the rapid development of online shopping platfprm, the security of logistics and transportation is important for the integrity of logistics system and shoping. Meanwhile, the application of Underwater Wireless Sensor Networks(UWSNs) for detecting environment secuity is more and more widely. In the marine logistics transportation, wharf and watercraft are the key focus of security monitoring in UWSNs. However, since the nodes can not be replaced at any time due to the complexity of the marine environment, the energy-efficiency technology of UWSNs faces enormous challenges.This paper investigates and analyzes the envionment of wharf and watercraft, presents a routing algorithm and sleeping schedule for UWSNs to save energy, which extend the network lifetime and improve the utilization of nodes. The main contribution of this paper is as follows:(1) Motivated by the importance of energy consumption in wharf of UWSNs, an energy-efficient data transmission scheme called EGRC(Energy-efficiency Grid Routing based on 3D Cubes) is proposed. First, the whole network model is regarded as a 3D cube from the grid point of view, and this 3D cube is divided into many small cubes, where a cube is seen as a cluster. Second, in order to make energy efficient and extend network lifetime, EGRC shapes an energy consumption model taking residual energy and location of sensor nodes into account to select the optimal cluster-heads. Moreover, EGRC utilizes residual energy, locations and end-to-end delay for searching for the next-hop node to maintain the reliability of data transmission. Simulation results show the effectiveness of EGRC, which performs better than related algorithms in terms of energy efficiency,reliability and end-to-end delay.(2) Focusing on the energy consumption of UWSNSs below watercraft, an Energy Balance sleeping schedule based on Particle Swarm optimization algorithm(EBPS) is proposed. EBPS considers residual energy, the distance from node to cluster and the number of neighbors to calculate the sleeping probability of node. What’s more, this paper not only presents a method for calculating the redundancy of node but also redefines the fitness function. This algorithm can detemine whether the node sleep or not by the residual energy of node, network coverage rate and the redundancy of node. Simulation results show that EBPS performs well in terms of energy efficiency and network lifetime.