A relay selection scheme based on the location of relay node was proposed for the selection problem in a multi-relay cooperative Spatial Modulation (SM) system, and the Bit Error Rate (BER) performance of the system was analyzed. The SM technique was used at the source node by the system, only one transmitting antenna was activated in each time slot, and based on the location information of the relay node, the Amplify Forward (AF) relay closest to the midpoint between the source node and the destination node was selected among all relays in each time slot for forwarding. The approach of moment generating function was used to derive the solution of the pairwise error probability of the system under Rayleigh fading channel, and therefore the theoretical BER of the system was given. Simulation results show that this relay selection method can achieve better BER performance of the system compared with the relay random selection and cyclic forwarding methods.

The channel estimation error seriously affects the key generation consistency of two communicating parties in the process of wireless key generation, a multi-bit quantization wireless key generation scheme under imperfect channel estimation condition was proposed. Firstly, in order to investigate the influence of imperfect channel estimation on wireless key generation, a channel estimation error model was established. Then, a multi-bit key quantizer with guard band was designed, and the performance of wireless key was able to be improved by optimizing the quantization parameters. The closed-form expressions of Key Disagreement Rate (KDR) and Effective Key Generation Rate (EKGR) were derived, and the relationships between pilot signal power, quantization order, guard bands and the above two key generation performance indicators were revealed. The simulation results show that, increasing the transmit pilot power can effectively reduce the KDR, and with the increasing of quantization order, the key generation rate can be improved, but the KDR also increases. Moreover, increasing the quantization order and choosing the appropriate guard band size at the same time can effectively reduce KDR.

To improve the efficiency of resource access in Software as a Service (SaaS) applications, a load balancing strategy combined with the important features of SaaS service was proposed. Firstly, the load balancing strategy was proposed by combining multi-tenancy and high scalability in SaaS service based on the distribution of request and global and local scalability. Secondly, the load balancing strategy model was constructed and simulated by a Petri net. Finally, this strategy was compared with Round Robin (RR), stochastic algorithm and Improved Least-Connection Scheduling (ILCS) load balancing algorithm in response time and throughput. The experimental results show that the response time and throughput of the proposed strategy become stable and they are superior to the other three algorithms after the request rate reaches 500 per second.

Through researching and analyzing the management and maintenance problems in virtual router platform, a three-layer virtual router architecture including control plane, forwarding plane and resource management plane was put forward. Control plane and forwarding plane were two basic function planes in virtual router, correspondingly carrying logical control plane and logical forwarding plane. In order to achieve dynamic management of virtual router, resource management plane was introduced. Resource management plane was regarded as one important function plane, which was used to manage and configure virtual router. The structure and mechanism of resource management plane were mainly expressed, and a prototype system to support static installment and dynamic adjustment of router instances was carried out. The experimental results prove that the maximum processing ability of resource management plane is about 3205 strategies/second, and it can complete establishment of router instance within one second, which can meet management requirements of virtual router platforms.

Currently, various image inpainting algorithms based on Curvature-Driven Diffusion (CDD) model only make use of the reference information of four neighborhood pixels. Therefore, they cannot keep shape edges and their inpainting precisions high enough. To conquer these difficulties, the image inpainting algorithm based on double-cross CDD was presented, in which the reference information for damaged pixel was extended from four into eight neighborhood pixels. Firstly, one inpainting value for damaged pixel could obtain from the reference information of four neighborhood pixels using the original CDD algorithm. Secondly, another new inpainting value was computed with the newly introduced four neighborhood pixels. Finally, the final inpainting value was a weighted mean of the above-mentioned two inpainting computational value. The proposed method, original CDD algorithm and its improved editions were implemented and compared in the experiments. The experimental results show that the proposed algorithm can effectively improve the inpainting precision and keep shape edges without increasing time complexity.

Currently, template size of texture-based image inpainting algorithm is fixed. Therefore, when the template size is small, the inpainting accuracy improves, but time complexity increases substantially; on the contrary, when the size is large, the time complexity declines, but inpainting error rate increases significantly. Adaptive template size algorithm proposed in this paper can enlarge template size according to the change of expect and variance of grayscale value between current template and its expanded one. Meanwhile, this approach can reduce template size according to the match degree between template and exemplar. After adaptively determining the template size, texture-based image inpainting algorithm was improved and used in experiments. The experimental results show this approach can highly improve the inpainting accuracy with high efficiency.

Software security measurement is critical to the development of software and improvement of software security. Based on the entropy and attack surface proposed by Manadhata et al. (MANADHATA P K, TAN K M C, MAXION R A, et al. An approach to measuring a system's attack surface, CMU-CS-07-146. Pittsburgh: Carnegie Mellon University, 2007; MANADHATA P K, WING J M. An attack surface metric. IEEE Transactions on Software Engineering, 2011, 37(3): 371-386), a method of software security measurement was used to assess the threat of the software's resources and provide the threat weight of these resources. Based on the threat weight, the attack surface metric was calculated for determining whether a software product is secure in design, or in what aspect the software product can be improved. The method is demonstrated in a case to show that, when using the method, the probable security threats can be found as early as possible to prevent from producing the software products that may have vulnerabilities, and the directions for the improvement of software security are pointed out clearly.

The low utilization of resource and the lack of reliability and scalability have always been the problems when business system is running in distributed environment. Concerning these problems, this paper designed a distributed business deployment platform based on Service-Oriented Architecture (SOA). Distributed business system could be automatically deployed on the platform, and the resource it needed would be dynamically assigned according to the state of service component, which implemented the dynamic extension and draw-back of the business ability. At the same time, double heat-computer backup, high available cluster and business migration mechanism were applied to guarantee the high reliability. The simulation results indicate that the platform achieves high resource utilization while the Quality of Service (QoS) is ensured.

GPU-based volume rendering has become an active research area in the domain of volume visualization. Large volume data cannot be uploaded directly due to the limitation of GPU memory, which has been a bottleneck of the application of GPU. Bricking method could not only solve this problem, but also maintain the quality of original volume-rendered image. However, the data exchange via the graphics bus is really time consuming and will definitely degrade the render performance. As for these difficulties, the optimal bricking for large volume data was calculated by establishing the model for optimal bricking, and also a 3D texture named node code texture was constructed and distance template was improved to accelerate the octree-based bricking volume rendering. The experimental results illustrate that the proposed method can significantly accelerate the bricking-based volume rendering for large volume data.