Duing to the satellite network has high requirement for security and fault-dealing ability, with Software Defined Network (SDN) technology introduced, the central controller was set in the network to enhance the network's fault-dealing ability. Firstly, a satellite network model was designed based on the SDN idea, and the satellite's operating parameters on the three-layer orbit were calculated and the constellations were built. Then, the method of hierarchical routing was used to design a fault tolerant routing mechanism for satellite network. Finally, the simulation experiments were carried out on the Mininet platform, and the experimental results of Fault-Tolerant Routing algorithm (FTR) were compared with the results of inter-Satellite Routing algorithm based on Link Recognizing (LRSR) and Multi-Layered Satellite Routing algorithm (MLSR). The comparison results show that in the case without damaged nodes or links in the network, the total routing delay of FTR is reduced by 6.06% on average compared with that of LRSR, which shows the effectiveness of introducing SDN centralized control; the packet loss rate of FTR is reduced by 25.79% compared with that of MLSR which also targets the minimum delay, which shows the effectiveness of temporary storage routing mechanism design for the Medium Earth Orbit (MEO) satellites. When the failure of nodes and links in the network is serious, FTR has the total routing delay 3.99% lower than LRSR and 19.19% lower than MLSR, and has the packet loss rate 16.94% lower than LRSR and 37.95% lower than MLSR, which shows the effectiveness of fault tolerance of FTR. The experimental results prove that the fault tolerant routing mechanism of satellite network based on SDN has better fault tolerant capability.

Aiming at the management requirement of real-time personnel statistics in office scenes with relatively fixed personnel positions, a laboratory personnel statistics and management system based on Faster Region-based Convolutional Neural Network (Faster R-CNN) and Intersection over Union (IoU) optimization was designed and implemented with an ordinary university laboratory as the example. Firstly, Faster R-CNN model was used to detect the heads of the people in the laboratory. Then, according to the output results of the model detection, the repeatedly detected targets were filtered by using IoU algorithm. Finally, a coordinate-based method was used to determine whether there were people at each workbench in the laboratory and store the corresponding data in the database. The main functions of the system are as follows:① real-time video surveillance and remote management of the laboratory; ② timed automatic photo, detection and acquisition of data to provide data support for the quantitative management of the laboratory; ③ laboratory personnel change data query and visualization. The experimental results show that the proposed laboratory personnel statistics and management system based on Faster R-CNN and IoU optimization can be used for real-time personnel statistics and remote management in office scenes.

To deal with the problems of the strategies for selecting the global best position and the low local search ability, a multi-objective particle swarm optimization algorithm based on global best position adaptive selection and local search named MOPSO-GL was proposed. During the guiding particles selection in MOPSO-GL, the Sigma method and crowding distance of the particle in the archive were used and the archive member chose the guided particles in the swarm to improve the solution diversity and the swarm uniformity. Therefore, the population might get close to the true Pareto optimal solutions uniformly and quickly. Furthermore, the improved chaotic optimization strategy based on Skew Tent map was adopted, to improve the local search ability and the convergence of MOPSO-GL when the search ability of MOPSO-GL got weak. The simulation results show that MOPSO-GL has better convergence and distribution.

In view of the deficiency of the existing weighted association rules mining algorithms which are not applied to deal with matrix-weighted data, a new pruning strategy of itemsets was given and the evaluation framework of matrix-weighted association patterns, SRCCCI (Support-Relevancy-Correlation Coefficient-Confidence-Interest), was introduced in this paper firstly, and then a novel mining algorithm, MWARM-SRCCCI (Matrix-Weighted Association Rules Mining based on SRCCCI), was proposed, which was used for mining matrix-weighted positive and negative patterns in databases. Using the new pruning technique and the evaluation standard of patterns, the algorithm could overcome the defects of the existing mining techniques, mine valid matrix-weighted positive and negative association rules, avoid the generation of ineffective and uninteresting patterns. Based on Chinese Web test dataset CWT200g (Chinese Web Test collection with 200GB web Pages) for the experimental data, MWARM-SRCCCI could make the biggest decline of its mining time by up to 74.74% compared with the existing no-weighted positive and negative association rules mining algorithms. The theoretical analysis and experimental results show that, the proposed algorithm has better pruning effect, which can reduce the number of candidate itemsets and mining time and improve mining efficiency markedly, and the association patterns of this algorithm can provide reliable query expansion terms for information retrieval.

Nowadays, many centificateless signature schemes depend on the honesty of Key Generation Center (KGC) excessively, so they also lose security guarantees when the KGC is dishonest. By analyzing the security of the certificateless signature scheme proposed by Liang Hongmei et. al. in security analysis and improvement of efficient certificateless signature scheme publicated by Journal fo Computer Applications, 2010,30(3):685-687, where the authors pointed out that the scheme could not resist public key replacement attack under negative dishonest KGC and positive dishonest KGCs attacks. Aiming at these problems, the scheme was improved by the means that KGC generated the users public key and made it public. The analysis of security shows that the improved scheme is able to resist public key replacement attack under negative dishonest KGC, thus successfully distinguishing the positive dishonesty of KGC,and resisting existential forgery on adaptively chosen message attack under the random oracle model.

Concerning that the resource in mobile Ad Hoc network is limited and the existing ant routing algorithms are complex, a basic ant routing algorithm was proposed. Based on the analysis of ant routing process, it only maintained basic ant routing mechanism, without any extra overhead, discussed pheromone update and pheromone use which were two key components of the algorithm; moreover, it analyzed their impact on performance by simulation. Finally, the experiment results show that it can get a performance closed to other routing protocols under a lower overhead.

QoS requirement is denoted by the range to support the flexible and heterogeneous QoS.According to the microeconomics theory and method,a Kelly/PSP model-based pricing strategy was presented to support the inter-group fairness.The ELSD(Equal Link Split Downstream) method was adopted to apportion the cost among group members,thus the intra-group fairness was provided.Based on the parallelized FCNN(Firing Coupled Neural Network),a parallel and intelligent QoS multicast routing algorithm was introduced,exploiting the inherent parallelism in FCNN fully and improving the scalability to the network size and the problem complexity significantly.Combining the above,a parallel,fair and intelligent QoS multicast routing mechanism was established.Simulation results have shown that the proposed mechanism is both effective and efficient,and the runtime efficiency of the proposed parallelized algorithm is higher than its corresponding serialized one.

An integrated QoS multicast routing algorithm in IP/DWDM optical Internet was discussed in this paper. Considering load balancing, given a multicast request and flexible QoS requirement, to find a QoS multicast routing tree is NP-hard. Thus, a hybrid algorithm based on simulated annealing and tabu search was introduced to construct the cost suboptimal QoS multicast routing tree, embedding the wavelength assignment procedure based on segment and wavelength graph ideas. Hence, the multicast routing and wavelength assignment was solved integratedly. Simulation results show that the proposed algorithm is both feasible and effective.

The Quality of Service(QoS) is one of the key problems of multimedia data transportation. However, the traditional Internet lacks dynamic QoS control mechanism. The overloading and underloading problem of the network were handled with proposing an Agent-based strategy to adjust the network resources, which was represented by bandwidth. Experiments proved the negotiation among user Agents could realize the optimized allocation of network resources.