Due to high carbon emissions in the logistics and distribution process, from a low carbon perspective, a Low Carbon Vehicle Routing Problem with Pickup and Delivery (LCVRPPD) considering fuzzy demand was formulated, and a 2-OPT based differential algorithm was proposed to solve the problem. In the algorithm, the natural number encoding method was adopted and three different fitness functions were given. Then, the 2-OPT algorithm was introduced to replace the original mutation mechanism of differential algorithm, and the binomial crossover operators and greedy selection operator were combined, so as to accelerate the convergence of the improved algorithm. In the case study, Taguchi method was used to determine reasonable values of parameters in the improved algorithm, and the SPSS (Statistical Product and Service Solutions) analysis revealed that the solution of the model with the minimum total cost as the objective function is the best compared to those of the other two different objective models of transportation cost minimization and carbon minimization respectively. For examples with different customer scales, compared with the basic differential algorithm, the improved algorithm has the total cost reduced by 1.8% to 3.0% and the carbon emission decreased by 0.7% to 3.5%; compared with genetic algorithm, the improved algorithm has the total cost reduced by 1.9% to 16.47% and the carbon emission decreased by 1.2% to 4.3%; compared with particle swarm optimization algorithm, the optimization effect is more obvious, the improved algorithm has the total cost reduced by 4.0% to 22.5% and the carbon emission decreased by 1.56% to 7.88%, which verify the effectiveness and advancement of the proposed algorithm. In summary, the proposed model and algorithm can provide a reference for the low carbon routing problem of pickup and delivery vehicles.

Aiming at the problems that it is difficult to improve performance and reduce power consumption in the process of High Level Synthesis (HLS), an automatic custom instructions identification method for high level synthesis was proposed. The enumeration and selection of custom instructions were implemented before high level synthesis, so as to provide a universal automatic custom instructions identification method for high level synthesis. Firstly, the high level source code was transformed into a Control Data Flow Graph (CDFG), and the source code was preprocessed. Secondly, a subgraph enumeration algorithm was used to enumerate all the connected convex subgraphs in a bottom-up manner from the Data Flow Graph (DFG) based on control data flow graph, which effectively improved the user's ability to flexibly modify the constraints. Then, considering the area, performance and code size, the subgraph selection algorithms were used to select partial optimal subgraphs as the final custom instructions. Finally, a new code was regenerated by incorporating the selected custom instructions as the input of high level synthesis. Compared with the traditional high level synthesis, the pattern selection based on frequency of occurrence reduced the area by an average of 19.1%. Meanwhile, the subgraph selection based on critical paths reduced the latency by an average of 22.3%. In addition, compared with Transitive Digraph (TD) algorithm, the enumeration efficiency of the proposed algorithm was increased by an average of 70.8%. The experimental results show that the automatic custom instructions identification method can significantly improve performance and reduce area and code size for high level synthesis in circuit design.

Aiming at the problems that a database is scanned for multiple times and a record is compared for many times to count in most frequent pattern mining algorithms for privacy-preserving, an Incremental Bitmap-based Randomized Response with Partial Hiding (IBRRPH) algorithm was proposed. Firstly, the bitmap technique was used to represent the transaction in the database, and the "and" operator for bit was used to speed up the support degree calculating. Secondly, an incremental update model was introduced by analyzing incremental access relationship, so that the mining result before was used to the maximum limit during incremental updating. The contrast experiment of performance to the algorithm proposed by Gu et al. (GU C, ZHU B P, ZHANG J K. Improved algorithm of privacy preserving association rule mining. Journal of Nanjing University of Aeronautics & Astronautics, 2015, 47(1):119-124) was done aiming at the increment range from 1000 to 40000. The experimental results show that the efficiency of the IBRRPH algorithm is improved over 21% compared to the algorithm proposed by Gu et al.

In view of the friend recommendation in Mobile Social Network (MSN), a new method based on multi-dimensional similarity was proposed. The method is a kind of method based on content, but not confined to single dimension matching information, it judges users' similarity of various dimensions from three aspects of space, time and interest, then gets a comprehensive judgment by "difference distance". The proposed method can recommend other users to target audience when they are consistent in geographical position, online-time and interest. The experimental results show that when the method is used in the friend recommendation of mobile social networks, its precision and efficiency are up to 80% and 60% respectively, the performance is much better than the other friend recommendation methods based on single dimension; at the same time, by adjusting the value of three dimensional weights, the method can be used in a variety of mobile social networks with different characteristics.

Considering that the Cooperative Cognitive Radio Networks (CCRN) perform poorly with low flexibility and deficient ability to adapt to complex environment, which caused by working under a fixed architecture at present, a kind of network architecture self-adaption technology based on cooperation and cognition was proposed to improve the anti-jamming and anti-damage ability of the CCRN. The technology made CCRN switch among three kinds of architectures, including centralized control, self-organization and cooperative relay, autonomously and flexibly, to deal with electromagnetic interference, equipment failure and obstructions on communication link, which could greatly enhance the network robustness. The switch scheme design and protocol implementation of different nodes were introduced in detail. Moreover, a CCRN testbed which consists of GNU Radio and the second generation of Universal Software Radio Peripheral (USRP2) was set up to test and verify its performance including switching time consumption and throughput. Results show that the technology significantly improves the anti-destroying ability, connectivity and Quality of Service (QoS) of CCRN compared with the network working under single, and fixed architecture.

Aiming at the problem that there is redundancy when using the greedy algorithm to solve the minimum MultiPoint Relay (MPR) set in the traditional Optimized Link State Routing (OLSR) protocol, a Global_OP_MPR algorithm based on the improvement of overall situation was proposed. First, an improved OP_MPR algorithm based on the greedy algorithm was introduced, and this algorithm removed the redundancy by gradually optimizing MPR set, which could simply and efficiently obtain the minimum MPR set; then on the basis of OP_MPR algorithm, the algorithm of Global_OP_MPR added the overall factors into MPR selection criteria to introduce "overall optimization" instead of "local optimization", which could eventually obtain the minimum MPR set in the entire network. Simulations were conducted on the OPNET using Random Waypoint motion model. In the simulation, compared with the traditional OLSR protocol, the OLSR protocol combined with OP_MPR algorithm and Global_OP_MPR algorithm effectively reduced the number of MPR nodes in the entire network, and had less network load to bear Topology Control (TC) grouping number and lower network delay. The simulation results show that the proposed algorithms including OP_MPR and Global_OP_MPR can optimize the size of the MPR set and improve the network performance of the protocol. In addition, due to taking the overall factors into consideration, Global_OP_MPR algorithm achieves a better network performance.

In open service grid,to establish trust relationships among different domains is a basic problem so as to cooperate between them.In this paper a two-layer trust model based on behavior was proposed to enhance grid security and extensibility.This trust model was used to resolve trust issues between entities in different domains.The upper layer established and maintained recommendation trust relationships between different domains in grid.Lower layer was in charge of how domain manager evaluated trust of entities in his domain.An algorithm was given to adjust trust relationships between domains based on entities interactions,and a practical method to process recommendation trust.At last,the experiment results show that two-layer trust model is effective and extensible.