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Aim at the problem for how to analyze the propensity to spread of shortage of supplies in emergency logistics decision support system, this paper proposed a new model to study the propensity to spread of shortage of supplies for emergency logistics network. This paper, by the mechanism of viral spreading and introducing the parameter of time "t", it constructed SI-SIRS ( susceptible infective and susceptible infective recover susceptible) model to analyze the scale-free network which included 61 nodes. Case analysis shows that SIRS effectively depicts the spread behavior of shortage of supplies in emergency logistics network. Propensities to spread of shortage of supplies are effected by node self-spread ability, network topology, individual nodes differences and responding mechanism of emergency logistics. [ABSTRACT FROM AUTHOR]

Community structure is one of the most important and basic topologic properties of complex network. The rational division of community structure in complex network is the main purpose of the complex network's community division research. This paper mainly researched the division of community structure in complex network based on the theory of supernetwork and standardized degree centrality. Based on the lack of GN algorithm, this paper proposed a new comprehensive algorithm to divide community structure from the perspective of supernetwork. Finally, the new comprehensive algorithm is illustrated through examples. [ABSTRACT FROM AUTHOR]

This paper proposed a labeling to data stream binding method independent of the contents of the packet, which based on packet delay modulation, and introducing the packet inter-arrival delay as the new labeling vector. The method used Himming code to achieve the label error control, designing the data packet randomized blocks, and modulated the packet delay time according to the label binding rules, then realized the implicit binding of security label to data stream. Based on this method, it solved the targeted attack problems caused by explicit binding method and its inflexibility. Theoretical analysis and experimental results demonstrate that the proposed method is robust against the network random timing perturbation and safety the binding security label when is transmitted in the network. [ABSTRACT FROM AUTHOR]

The ranges of state variable value of transition system are large, and the state space of system transition, but the transitions of the system are often unpredictable. This paper defined the concepts: initial safety states, safety transition condition, safety state, safety action, safety run and safety transition system, and proved the all states in safety transition system were safe. Then it used it to remold the network transition system, and changed it a safety transition system. [ABSTRACT FROM AUTHOR]

Analyzing the user behavior is of great importance to the management and control of network users. User behavior, which is actually s set of data exchanges, is ultimately displayed as traffic flow, showing regularity along time. This paper explored this regularity through studying the timing relationship between traffic flows, and proposed a novel user behavior analysis method. The proposed method utilized three steps, which were based on fractal model, improved maximum distance clustering method, and Apriori algorithm for segmentation, clustering, and timing analysis, respectively, to obtain the user behavior regularity from user data exchange. Theoretic analysis and simulation results illustrate that this method can satisfactorily classify the packet sequence and discover the regularity of user transmit behavior without decrypting user information. [ABSTRACT FROM AUTHOR]

To solve the problems of low efficiency and more redundant messages in unstructured P2P network resources search, this paper proposed an ant colony optimization based on interest factor(IACO). It gave full consideration to the effects of node value of resources search. It introduced node interest factor into traditional ant colony algorithm to adjust the weight relationship of node value and pheromones dynamically in the forward probability calculation, and effectively guided the generation of resources query path. The simulation results show that the proposed algorithm can improve the success significantly rate and to a certain extent can reduce the amount of redundant messages in the network at the same time. [ABSTRACT FROM AUTHOR]

In P2P network, performances of many nodes in Chord algorithm are inconsonant. The problem that nodes leave and join frequently will restrict the performance of system seriously. Therefore, this paper presented grouping improved algorithm based on related degree of information. It introduced the concept of the node information relevant degree in the algorithm, in which the original Chord was adjusted by group on the related degree of information. Then the super group was connected through the super nodes. It selected two super nodes from each group and constitute a super group. In the meantime, every node was increased a counter-clockwise route. Then they could choose the shortest path to find two super nodes in both clockwise and counterclockwise direction. The experiments show that performance and adaptability of system are strengthened by the improved algorithm. The search efficiency of Chord in P2P network is improved. [ABSTRACT FROM AUTHOR]

In order to solve the defects of retransmission for random network coding, this paper presented a retransmission approach FMWBR based on local random coding parameter which was combined with Fourier matrix and random network coding. A row vector of the Fouier matrix shared with a source node and a receiver node acted as a coding vector and a decoding vector, which ensured the retransmission packets' solvability. The head of retransmission packets only included the number of the row vector in the Fourier matrix. The theoretic analysis shows that TMWBR enhances the security of wireless transmission, improves the robustness of networks and reduces the cost of packets' head. The simulation results indicate that comparing with traditional scheme, the scheme effectively reduces the average number of transmission and the overhead of networks, improves networks' throughput. [ABSTRACT FROM AUTHOR]

This paper proposed the job scheduling algorithm ( ISS) and optimization of dynamic data replication algorithm ( ODHRA) for effectively conducting job scheduling and data replication, and built a program to effectively combine the two algorithms, in order to reduce the execution time of job. First, this program used ISS algorithm to give a comprehensive consideration to the number of jobs waiting in queue, the location of required data for the job and the computing capacity of sites, and used a hierarchical scheduling of network structure with appropriate weighting coefficient to calculate the comprehensive job cost and search for an optimum computing node area; next, it used ODHRA algorithm to analyze data transfer time, storage access latency as well as replica requests that waiting in the storage queue and the distance between nodes, selected the best replica location from many replicas, and then combined replica placement and replica management to reduce the file access time. The simulation results demonstrate that the proposed replication and scheduling strategies give better performance than the other algorithms in the mean execution time of job. [ABSTRACT FROM AUTHOR]

This paper presented a novel ubiquitous knowledge cloud model based on Cloud-P2P network platform, which organized the various types of documents, knowledge orderly together, and took full account of the available resources of network edge. In the premise of protecting user's experience, the model made the tasks about knowledge requirement submitted from users migrate from the network servers to the nodes of network edge. To further improve the users' satisfaction, it proposed a new dynamic complex adaptive quality of service protection mechanism, which provided an effective solution of the problem of server performance bottleneck in peak time existing in the traditional knowledge systems through differentiating the different types of users and setting the threshold of server load. [ABSTRACT FROM AUTHOR]