Liu Linfeng

Coverage Optimization Algorithm Based on Sampling for 3D Underwater Sensor Networks

We discuss the problem of maximizing the sensor field coverage for a specific number of sensors while minimizing the distance traveled by the sensor nodes. Thus, we define the movement task as an optimization problem that involves the adjustment of sensor node positions in a coverage optimization mission. We propose a coverage optimization algorithm based on sampling to enhance the coverage of 3D underwater sensor networks. The proposed coverage optimization algorithm is inspired by the simple random sampling in probability theory. The main objective of this study is to lessen computation complexity by dimension reduction, which is composed of two detailed steps. First, the coverage problem in 3D space is converted into a 2D plane for heterogeneous networks via sampling plane in the target 3D space. Second, the optimization in the 2D plane is converted into an optimization in a line segment by using the line sampling method in the sample plane. We establish a quadratic programming mathematical model to optimize the line segment coverage according to the intersection between sensing circles and line segments while minimizing the moving distance of the nodes. The intersection among sensors is decreased to increase the coverage rate, while the effective sensor positions are identified. Simulation results show the effectiveness of the proposed approach.We discuss the problem of maximizing the sensor field coverage for a specific number of sensors while minimizing the distance traveled by the sensor nodes.Thus, we define the movement task as an optimization problem that involves the adjustment of sensor node positions in a coverage optimization mission. We propose a coverage optimization algorithm based on sampling to enhance the coverage of 3D underwater sensor networks. The proposed coverage optimization algorithm is inspired by the simple random sampling in probability theory.Themain objective of this study is to lessen computation complexity by dimension reduction, which is composed of two detailed steps. First, the coverage problem in 3D space is converted into a 2D plane for heterogeneous networks via sampling plane in the target 3D space. Second, the optimization in the 2D plane is converted into an optimization in a line segment by using the line sampling method in the sample plane. We establish a quadratic programming mathematical model to optimize the line segment coverage according to the intersection between sensing circles and line segments while minimizing the moving distance of the nodes. The intersection among sensors is decreased to increase the coverage rate, while the effective sensor positions are identified. Simulation results show the effectiveness of the proposed approach.

Image compression scheme based on PCA for wireless multimedia sensor networks

Abstract In combination of the characteristic of the network architecture of wireless multimedia sensor networks (WMSNs), a distributed multi-node cooperative network (DMCN) model is designed by using the concept of in-network processing to improve their energy, memory and computational power. To balance the energy consumption of the network, according to roles division, camera nodes and common nodes are cooperated to accomplish the workload of image acquisition, compression and transmission. Camera nodes gather images and send blocking images to the common nodes in cluster. Common nodes adaptively compress the partitioned images by using a noise-tolerant distributed image compression (NDIC) algorithm based on principal component analysis (PCA) called NDIC-PCA algorithm and send the compressed data to the cluster head node. Then, the cluster head node sends the compressed image data to the station. Simulation results demonstrate that, DCNM can effectively balance the energy consumption of network and largely extend the network lifecycle. In addition, compared with previous algorithms, the proposed NDIC-PCA algorithm achieves higher peak signal to noise ratio without decreasing compression ratio.

New spray and wait protocol with node activity in heterogeneous delay tolerant networks

Abstract The spray and wait protocol is a classic copy-limited spraying protocol in delay tolerant networks, in which, the binary spray mode can be improved for heterogeneous delay tolerant networks. In this article, a new conception of node activity was defined to weigh the importance of nodes in aspect of message dissemination in the whole network. A new spray and wait protocol with node activity was proposed to improve the performance in heterogeneous delay tolerant networks. A mathematical model used under varieties of the spraying protocols was also proposed to analyze the expected delay of the protocol. Simulations show that the spray token proportion with node activity is optimal and the new protocol is of better performance than other related protocols. Therefore, this protocol has high efficiency and good scalability.