Guoyin Zhang

A Trust Model Based on Subjective Logic

In order to resolve the trust problem due to the opening, the dynamics, the anonymity and uncertainty of p2p system, this paper proposes a new p2p trust model by analyzing and improving the subjective logic, a new trust quantification formula with the negative events effect and the time effect is given, and a definition of risk is also presented, By doing this, we can evaluate the trust relationships between peers more precisely and prevent the hidden security dangers of cooperative cheat and slander more effectively, thus can resolve security problems exist in p2p environment more effectively.

Application research on network coding in WSN

This paper introduces the characteristics of the wireless network, including self-organizing, dynamic topology, wireless communications and so on, which make the network nodes have limited energy, the same as processing power, storage capacity and communication capabilities, therefore, the efficient use of energy, maximizing its network cycle is the wireless sensor networks core issue. Network coding integrates the concept of routing and coding, which has been proven to be able to approach the theoretical transfer limit of the network capacity. The unreliability of wireless link and the broadcasting characteristics of physical layer are ideal for the use of network coding. This paper reviews the applications of network coding technology in wireless sensor network, including improving network throughput, reducing energy consumption, increasing the reliability and security of the network link, and improving the efficiency of data aggregation.

Minimal Increase Network Coding for Dynamic Networks

Because of the mobility, computing power and changeable topology of dynamic networks, it is difficult for random linear network coding (RLNC) in static networks to satisfy the requirements of dynamic networks. To alleviate this problem, a minimal increase network coding (MINC) algorithm is proposed. By identifying the nonzero elements of an encoding vector, it selects blocks to be encoded on the basis of relationship between the nonzero elements that the controls changes in the degrees of the blocks; then, the encoding time is shortened in a dynamic network. The results of simulations show that, compared with existing encoding algorithms, the MINC algorithm provides reduced computational complexity of encoding and an increased probability of delivery.

Cluster Ensemble Based Image Segmentation Algorithm

By integrating image segmentations to form a final image cluster is an effective image process, called image cluster ensemble. The image processing improves the accuracy and stability from traditional single clustering based algorithm. In the paper, we design a novel image partition algorithm, called Cluster Ensemble algorithm by using the K-Means and Nyström Spectral Clustering (CEKMNSC). The algorithm requires low computational complexity. It adopts a cluster ensemble scheme. In clustering, the algorithm uses a k-means algorithm to create a set of segmentations results. In ensemble processing, the algorithm integrates partition results based on the Nyström method. Our experimental results show that CEKMNSC algorithm has higher quality of clustering.

Image Segmentation: A Novel Cluster Ensemble Algorithm

Cluster ensemble has testified to be a good choice for addressing cluster analysis issues, which is composed of two processes: creating a group of clustering results from a same data set and then combining these results into a final clustering results. How to integrate these results to produce a final one is a significant issue for cluster ensemble. This combination process aims to improve the quality of individual data clustering results. A novel image segmentation algorithm using the Binary k-means and the Adaptive Affinity Propagation clustering (CEBAAP) is designed in this paper. It uses a Binary k-means method to generate a set of clustering results and develops an Adaptive Affinity Propagation clustering to combine these results. The experiments results show that CEBAAP has good image partition effect.

The Transformation and Optimization in IR2VHDL

Reconfigurable computing technology can be used to improve the parallelism of computing. The reconfigurable compiler can be implemented to support the systems parallelism and flexibility without redesigning original program. The IR2VHDL (VHSIC Hardware Description Language) is one of the core components of the reconfigurable compiler. In this paper, we deploy IR2VHDL to LLVM (Low Level Virtual Machine) - IR (Intermediate Representation) in order to achieve hardware-oriented optimization for improving system parallelism and robustness. The deployment is very useful when LLVM-IR is transformed. Finally, taking bubble sort program as a test-bed, the process of transformation and optimization are tested to study eh applicability and feasibility of IR2VHDL.

Research on Program Execution Time Assessment of LLVM IR Program

Program performance assessment is one of important methods to optimize a system design. The assessment of program execution time is always key topic in computer structure. A good assessment can provide important measure basis for hardware/software automatic partitioning in reconfigurable computer compiler. This paper analyzes the characteristics of IR program and proposes an IR layer program classification algorithm for assessing the program execution time. The method can provide an accurate measure and can be constructed into a BP neural network assessment system. The experimental results show that the proposed assessment model has lower assessment deviation compared to other models under the same conditions. The BP neural network model can be trained.

A Partial Network Coding Scheme Based on Energy-Balancing in WSN

This paper provides a new partial network coding scheme suitable for WSN. The sensor nodes of this scheme include four states: Normal, Coding, Suspend and Sleep. Transformation between these states is energy-oriented and relevant scheme are divided into three steps: Initiate coding, Check Period and Balance energy. First, the paper describes the designing process of this scheme, and then describes the coding and decoding process of random linear network coding used in this paper. At last, according to the result of the NS2 virtual experiment, this scheme exceed traditional network coding schemes: increasing the efficiency of network resource usage, decreasing network lag and expanding living period of WSN.

Double-Layer Evolvable Hardware Method

One of the bottlenecks in traditional evolvable hardware is that the fitness evaluation process is restricted by the performance of the reconfigurable hardware, so that the overall evolution efficiency is very low. In order to solve the problem we propose a double-layer evolvable hardware method, which is composed of logical evolving layer and physical evolving layer. The chromosome coding based on the logic operation unit is used in logical evolving, which can implement the rapid fitness evaluation process in computer without the FPGA and other hardware. Based on the result of logical evolving, the physical evolving uses classical evolving method to evolve the physical characters of target circuit. Thus, the efficiency and the popularity of the evolvable hardware can both be improved.

Design and Routing Algorithm of PPCAN

By analyzing existed improved DHT networks, we propose a novel improved CAN: PPCAN, which adopt 2-dimensional Polar coordinate and power series expand subspace hops to obtain better routing efficiency and lower maintenance cost. Then, we introduce the Landmarks to optimize the relay sequenced peers through the hops. Our design can be implemented entirely at the application level. Some improved routing algorithms based CAN also can be implemented in PPCAN.