In order to meet the requirements of high reliability and low latency in the 5G network environment， and reduce the resource consumption of network bandwidth at the same time， a Service Function Chain （SFC） deployment method based on node comprehensive importance ranking for traffic and reliability optimization was proposed. Firstly， Virtualized Network Function （VNF） was aggregated based on the rate of traffic change， which reduced the deployed physical nodes and improved link reliability. Secondly， node comprehensive importance was defined by the degree， reliability， comprehensive delay and link hop account of the node in order to sort the physical nodes. Then， the VNFs were mapped to the underlying physical nodes in turn. At the same time， by restricting the number of links， the “ping-pong effect” was reduced and the traffic was optimized. Finally， the virtual link was mapped through k-shortest path algorithm to complete the deployment of the entire SFC. Compared with the original aggregation method， the proposed method has the SFC reliability improved by 2%， the end-to-end delay of SFC reduced by 22%， the bandwidth overhead reduced by 29%， and the average long-term revenue-to-cost ratio increased by 16%. Experimental results show that the proposed method can effectively improve the link reliability， reduce end-to-end delay and bandwidth resource consumption， and play a good optimization effect.

Aiming at the problem that most mapping algorithms based on virtual Software Defined Network （vSDN） do not fully consider the correlation between nodes and links， a vSDN mapping algorithm based on network topology segmentation and clustering analysis was proposed. Firstly， the complexity of physical network was reduced by the topology segmentation method based on the shortest hop count. Then， the request acceptance rate of mapping algorithm was improved by the clustering analysis method based on node topology and resource attributes. Finally， the nodes that do not meet the link requirements were remapped， by dispersing the link constraints to the bandwidth resources of nodes and the degrees of nodes to perform the consideration with constraints， so that the mapping process between nodes and links was optimized. Experimental results show that， the proposed algorithm can effectively improves the request acceptance rate of virtual network mapping algorithm based on Software Defined Network （SDN） architecture in physical networks with low connectivity probability.

In order to meet the requirements of high speed and multi-channel of data acquisition and transmission for γ-ray industrial Computed Tomography (CT), the system based on User Datagram Protocol (UDP) with Field-Programmable Gate Array (FPGA) controlling was designed. This system increased FPGA counting unit, so more channels could be used for data collection. Main control was based on FPGA as the core, which used UDP protocol and was implemented by Verilog programming. Then, data was transmitted to upper computer for image reconstruction by Ethernet interface chip. The upper computer interface and mutual communication with the underlying transmission circuit realized by VC ++ 6.0 programming. The experimental results indicate that, in the 100 Mb/s full-duplex mode, the network utilization rate can reach 93%, and transmission speed is 93 Mb/s (11.625 MB/s), and the upper computer can receive data correctly in a long distance. So, it can satisfy the system requirements of rapid speed and long distance for γ-ray industrial CT.

An image decomposition based on minimizing the variational function with L0-norm regularization using local gradient was proposed, with regard to the problem that difference between gradient of the noise and gradient of the edge cannot be discriminated by the typical gradient computed from the first-order derivative. It consisted of fidelity term and regular term, and the regular term was estimated by the L0-norm of local gradient from the first-order derivative. Finally, the base layer, only including edges and excluding noises, was obtained by minimizing the proposed variational function. Compared with the decomposition algorithm with the typical L0 gradient regulation, the proposed algorithm can preserve sharp edges and avoid the impact of noises.

Concerning the disadvantages of quality assessment algorithms for color images, a new algorithm based on visual structural similarity was proposed. Firstly, testing images were transformed into a selected uniform color space LAB2000HL. Secondly, one luminance Contrast Sensitivity Function (CSF) and two chromatic CSFs were used to filter images respectively. Thirdly, three structural similarity indexes were computed by multi-scale structural similarity index measurement (M-SSIM). Lastly, the proposed algorithm was constructed by weighting the three structural similarity indexes， which depended on different visual sensitivities of luminance and chromaticity. In the experiment, testing results on TID2008 database were compared with the results of visual assessment by Spearman rank-order correlation coefficient and Kendall rank-order correlation coefficient. The experimental results show that the proposed algorithm is more consistent with visual assessment and outperforms several other popular image quality assessment algorithms.

For resolving the problem of curvature calculation for scattered point cloud data with strong noise, a robust statistics approach to curvature estimation was presented. Firstly the local shape at a sample point in 3D space was fitted by a quadratic surface. In addition,the fitting was performed at multiple times with randomly sampled subsets of points, and the best fitting result evaluated by variable-bandwidth maximum kernel density estimator was obtained. At last, the sample point was projected onto the best fitted surface and the curvatures of the projected point was estimated. The experimental results demonstrate that the proposed method is robust to noise and outliers. Especially with increasing noise variance, the proposed method is significantly better than the traditional parabolic fitting method.

Image splicing is a technique commonly used in image tampering. To implement image splicing blind detection，a new splicing detection scheme was proposed. Image splicing detection could be regarded as a two-class pattern recognition problem and the model was established based on moment features and some Image Quality Metrics (IQMs) extracted from the given test image. This model could measure statistical differences between original image and spliced image. Kernel-based Support Vector Machine (SVM) was chosen as a classifier to train and test the given images. Experimental results demonstrate that this new splicing detection scheme has some advantages of high-accuracy and wide-application.

The existing fuzzy Active Queue Management (AQM) mechanisms mostly consider the queue length and its change rate as fuzzy inputs, while rarely consider the effect of packet arriving rate together. In order to design a more effective AQM algorithm, a novel fuzzy AQM algorithm called FQL-AQM was proposed. FQL-AQM considered both real queue length and average traffic load factor as fuzzy inputs, and regulated packet dropping probability through a fuzzy self-tuning algorithm. This algorithm can keep the queue length stable at the reference queue length level, and keep the average load factor stable at 1. And FQL-AQM can be well applied to a variety of network environments and can improve the network robustness. Simulation results show that FQL-AQM algorithm is efficient, stable and outperforms other proposed AQM algorithms in response rate, link utilization ratio, and queue length stability.

The advantages and disadvantages of TCP Westwood (TCPW) algorithm were analyzed, especially when it was used in Geostationary Earth Orbit (GEO) satellite networks. In order to solve the existing problems, a new improved TCPW (TCPW-N) algorithm considering loss differentiation was proposed. TCPW-N algorithm took full advantage of Vegas, Veno and the existing improved TCPW algorithm (namely LogWestwood+), and TCPW-N was suitable for GEO satellite networks. TCPW-N algorithm can judge the packet loss reason, and adjust the congestion window according to the different packet loss reasons and the estimated network bandwidth. Performance analysis and simulation results show that TCPW-N algorithm has effectively resolved the existing problems of TCPW. Compared with TCPW and its other improved algorithm, TCPW-N algorithm has better throughput performance, lower packet loss rate, and better fairness and friendliness when applied to GEO satellite networks.

Breaking out of network worms brings a tremendous damage to the Internet. Launch the worm defense and response can improve network anti-strike capability. Tracing worm propagation path after its outbreak can reconstruct not only the earliest infected nodes but also the timing order of victims been infected. For the detection and defense of large scale Internet worm outbreaks, a convenient and safety experimental environment that capable of running real worm become an important work to observe large scale worm infection, intrusion and propagation, it can be a large scale worm testbed for forensic evidence. This paper presents a large-scale worm propagation experiments environment for tracing algorithm, which is an isolation environment that can run related experiments. To conform as much as really to the actual network, the experimental environment use virtual machine technology, simulate a large number of hosts and network equipments attend. According to the actual worm, this environment can trigger large-scale worm outbreaks within the controllable scope of human, observe propagation process of the worm, experiment detection and defense techniques, discover worm propagation characteristic such as scanning method and propagation process, real-time collect network traffic and propagation process, investigate network traffic, launch speculate algorithm for reconstructing out patient zero and propagation path of the worm. Then actual worm propagation process can be captured and compared with the results using tracing algorithm.