网点网络也智能——锐捷助力网点网络改造

日前，锐捷网络（原实达网络）在中国工商银行江苏省分行网点网络改造项目中成功中标，其具有高性能、高可靠性和易管理性等多方面优势的交换机在江苏工行网点网络改造中实现了大规模应用。

充分发挥网点网络优势 推进农村金融服务全覆盖

本文介绍了农行蔡甸支行在服务"三农"方面充分发挥网点网络优势,加强网点服务功能建设,加大移民金融服务和新农保等重点项目实施力度的做法,为农行服务"三农"提供了借鉴。

Sensor deployment strategy for chain-type wireless underground mine sensor network

Wireless sensor networks (WSNs) are very important for monitoring underground mine safety. Sensor node deployment affects the performances of WSNs. In our study, a chain-type wireless underground mine sensor network (CWUMSN) is first pre- sented. A CWUMSN can monitor the environment and locate miners in underground mines. The lowest density deployment strate- gies of cluster head nodes are discussed theoretically. We prove that the lifetime of CWUMSN with a non-uniform deployment strategy is longer than with a uniform deployment strategy. Secondly, we present the algorithm of non-uniform lowest density de- ployment of cluster head nodes. Next, we propose a dynamic choice algorithm of cluster head nodes for CWUMSN which can im- prove the adaptability of networks. Our experiments of CWUMSN with both non-uniform lowest density and uniform lowest den- sity deployments are simulated. The results show that the lifetime of CWUMSN with non-uniform lowest density deployment is almost 2.5 times as long as that of the uniform lowest density deployment. This work provides a new deployment strategy for wire- less underground mine sensor networks and then effectively promotes the application of wireless sensor networks to underground mines.

SiamADN:Siamese Attentional Dense Network for UAV Object Tracking

Single object tracking based on deep learning has achieved the advanced performance in many applications of computer vision.However,the existing trackers have certain limitations owing to deformation,occlusion,movement and some other conditions.We propose a siamese attentional dense network called SiamADN in an end-to-end offline manner,especially aiming at unmanned aerial vehicle(UAV)tracking.First,it applies a dense network to reduce vanishing-gradient,which strengthens the features transfer.Second,the channel attention mechanism is involved into the Densenet structure,in order to focus on the possible key regions.The advance corner detection network is introduced to improve the following tracking process.Extensive experiments are carried out on four mainly tracking benchmarks as OTB-2015,UAV123,LaSOT and VOT.The accuracy rate on UAV123 is 78.9%,and the running speed is 32 frame per second(FPS),which demonstrates its efficiency in the practical real application.

A load-balanced minimum energy routing algorithm for Wireless Ad Hoc Sensor Networks

Wireless Ad Hoc Sensor Networks (WSNs) have received considerable academia research attention at present. The energy-constraint sensor nodes in WSNs operate on limited batteries, so it is a very important issue to use energy efficiently and reduce power consumption. To maximize the network lifetime, it is essential to prolong each individual node’s lifetime through minimizing the transmission energy consumption, so that many minimum energy routing schemes for traditional mobile ad hoc network have been developed for this reason. This paper presents a novel minimum energy routing algorithm named Load-Balanced Minimum Energy Routing (LBMER) for WSNs considering both sensor nodes’ energy consumption status and the sensor nodes’ hierarchical congestion levels, which uses mixture of energy balance and traffic balance to solve the problem of “hot spots” of WSNs and avoid the situation of “hot spots” sensor nodes using their energy at much higher rate and die much faster than the other nodes. The path router established by LBMER will not be very congested and the traffic will be distributed evenly in the WSNs. Simulation results verified that the LBMER performance is better than that of Min-Hop routing and the existing minimum energy routing scheme MTPR (Total Transmission Power Routing).

Analysis of distribution uniformity of nodes in wireless sensor networks

Wireless sensor networks have several special characteristics which make against the network coverage, such as shortage of energy, difficulty with energy supply and so on. In order to prolong the lifetime of wireless sensor networks, it is necessary to balance the whole network load. As the energy consumption is related to the situation of nodes, the distribution uniformity must be considered. In this paper, a new model is proposed to evaluate the nodes distribution uniformity by considering some parameters which include compression discrepancy, sparseness discrepancy, self discrepancy, maximum cavity radius and minimum cavity radius. The simulation results show that the presented model could be helpful for measuring the distribution uniformity of nodes scattered randomly in wireless sensor networks.

An Iterative Clustering-Based Localization Algorithm for Wireless Sensor Networks

In wireless sensor networks,node localization is a fundamental middleware service.In this paper,a robust and accurate localization algorithm is proposed,which uses a novel iterative clustering model to obtain the most representative intersection points between every two circles and use them to estimate the position of unknown nodes.Simulation results demonstrate that the proposed algorithm outperforms other localization schemes (such as Min-Max,etc.) in accuracy,scalability and gross error tolerance.

Kaixin001 Network with Random Hierarchical Model

A new random hierarchical model to describe the neighborhood properties of Kaixin001 network is developed in this paper. The degree distribution of this network model follows P（k） k-γ with y = 1. It means the network model has a power-law distribution. Through calculating the clustering coefficients and average path length （APL）, the result reflects that the model has the properties of high clustering coefficients and low APL.

A Secure and Pragmatic Routing Protocol for Mobile Ad hoc Networks

An ad hoc network is a group of wireless mobile computers(or nodes),in which individual nodes cooperate by forwarding packets for each other to allow nodes to communicate beyond direct wireless transmission range.Because of node mobility and power limitations,the network topology changes frequently.Routing protocol plays an important role in the ad hoc network.A recent trend in ad hoc network routing is the reactive on-demand philosophy where routes are established only when required.As an optimization for the current Dynamic Source Routing Protocol,a secure and pragmatic routes selection scheme based on Reputation Systems was proposed.We design the Secure and Pragmatic Routing protocol and implement simulation models using GloMoSim.Simulation results show that the Secure and Pragmatic Routing protocol provides better experimental results on packet delivery ratio,power consumption and system throughput than Dynamic Source Routing Protocol.

Mathematical Modeling in Social Network Analysis： Using TOPSIS to Find Node Influences in a Social Network

In a social network analysis the output provided includes many measures and metrics. For each of these measures and metric, the output provides the ability to obtain a rank ordering of the nodes in terms of these measures. We might use this information in decision making concerning disrupting or deceiving a given network. All is fine when all the measures indicate the same node as the key or influential node. What happens when the measures indicate different key nodes？ Our goal in this paper is to explore two methodologies to identify the key players or nodes in a given network. We apply TOPSIS to analyze these outputs to find the most influential nodes as a function of the decision makers＇ inputs as a process to consider both subjective and objectives inputs through pairwise comparison matrices. We illustrate our results using two common networks from the literature： the Kite network and the Information flow network from Knoke and Wood. We discuss some basic sensitivity analysis can may be applied to the methods. We find the use of TOPSIS as a flexible method to weight the criterion based upon the decision makers＇ inputs or the topology of the network.

MOBILITY AIDED LOCALIZATION OF WIRELESS SENSOR NETWORKS WITH INACCURATE RANGE MEASUREMENTS

This paper studies the relationship between mobility, navigation and localization in the context of wireless sensor networks with mobile beacons. It is observed that mobility can aid in network node localization and that once localized, the network nodes can localize and track a mobile object and guide its navigation. A distributed kernel-based algorithm is proposed that enables the nodes to establish confident position estimates in the presence of ranging inaccuracies. The proposed approach features robustness with respect to range measurement inaccuracies, low complexity and distributed implementation, using only local information. Simulation validates our approach viable.

A brief analysis of the phase transitions and the overall correlation behavior in non uniformity computer network

With the developing of the computer, the network is more and more liked by the users. It has become an indispensable part of the living and production. However, with the expanding of network scale, there have been some problems in the operation of the network system. Most of people lack of understanding on these issues, so they couldn＇ t handle them well. Some people use the theory of phase transitions to explain the power law phenomena in computer network. But it only start from the theory, but ignores the correlation of network nodes. The lack of holistic thinking mode, make the development of computer network get into a stray area. This paper started from the phase transition theory, elaborated the connotations of phase transformation and the overall correlation, and described the problems about them.

A Weighted Evolving Network with Community Size Preferential Attachment

Community structure is an important characteristic in real complex network.It is a network consists ofgroups of nodes within which links are dense but among which links are sparse.In this paper, the evolving network includenode, link and community growth and we apply the community size preferential attachment and strength preferentialattachment to a growing weighted network model and utilize weight assigning mechanism from BBV model.Theresulting network reflects the intrinsic community structure with generalized power-law distributions of nodes'degreesand strengths.

An Overlay Network for Monitoring Activities of Computer Viruses

To accurately track computer viruses,an overlay network that monitors the activities of viruses is constructed.Identifying and locating nodes infected by virus on network is achieved by a naming system in which a node in the network is mapped to a unique serial number of the hard-drive.By carefully monitoring and recording sensitive communication between local system and remote nodes on the network,and suspicious operations on files that originate from remote nodes and entered via some form of file transfer,activities of viruses in both local and network level are recorded and ready for future analysis.These data can also be used in analysis of the mechanism of a computer virus as well as its spreading mode and pattern.

Computing All Pairs Shortest Paths on Sparse Graphs with Articulation Points

In most network analysis tools the computation of the shortest paths between all pairs of nodes is a fundamental step to the discovery of other properties. Among other properties is the computation of closeness centrality, a measure of the nodes that shows how central a vertex is on a given network. In this paper, the authors present a method to compute the All Pairs Shortest Paths on graphs that present two characteristics： abundance of nodes with degree value one, and existence of articulation points along the graph. These characteristics are present in many real life networks especially in networks that show a power law degree distribution as is the case of biological networks. The authors＇ method compacts the single nodes to their source, and then by using the network articulation points it disconnects the network and computes the shortest paths in the biconnected components. At the final step the authors proposed methods merges the results to provide the whole network shortest paths. The authors＇ method achieves remarkable speedup compared to state of the art methods to compute the shortest paths, as much as 7 fold speed up in artificial graphs and 3.25 fold speed up in real application graphs. The authors＇ performance improvement is unlike previous research as it does not involve elaborated setups since the authors algorithm can process significant instances on a popular workstation.

A TWO-LAYER RECURRENT NEURAL NETWORK BASED APPROACH FOR OVERLAY MULTICAST

Overlay multicast has become one of the most promising multicast solutions for IP network,and Neutral Network(NN) has been a good candidate for searching optimal solutions to the constrained shortest routing path in virtue of its powerful capacity for parallel computation. Though traditional Hopfield NN can tackle the optimization problem,it is incapable of dealing with large scale networks due to the large number of neurons. In this paper,a neural network for overlay multicast tree com-putation is presented to reliably implement routing algorithm in real time. The neural network is constructed as a two-layer recurrent architecture,which is comprised of Independent Variable Neurons(IDVN) and Dependent Variable Neurons(DVN) ,according to the independence of the decision variables associated with the edges in directed graph. Compared with the heuristic routing algorithms,it is characterized as shorter computational time,fewer neurons,and better precision.

Lossy nodes inference based on end-to-end passive monitoring in wireless sensor networks

This paper presents a passive monitoring mechanism, loss）, nodes inference （LoNI）, to identify loss）, nodes in wireless sensor network using end-to-end application traffic. Given topology dynamics and bandwidth constraints, a space-efficient packet marking scheme is first introduced. The scheme uses a Bloom filter as a compression tool so that path information can bc piggybacked by data packets. Based on the path information, LoNI then adopts a fast algorithm to detect lossy nodes. The algorithm formulates the inference problem as a weighted set-cover problem and solves it using a greedy approach with low complexity. Simulations show that LoNI can locate about 80% of lossy nodes when lossy nodes are rare in the network. Furthermore, LoNI performs better for the lossy nodes near the sink or with higher loss rates.

A Novel Optical Burst Mesh Network with Optical Time Slot Interchange at Source Nodes

In this paper, we propose an optical burst network architecture supporting the ge- netic mesh topology. The intermediate node architecture of the mesh network can be the same with current wavelength switching Wave- length Division Multiplexing （WDM） net- works, and thus can reuse existing deployed infrastructure. We employ a novel Optical Time Slot Interchange （OTSI） at the source nodes for the first time to mitigate the burst conten- tion and to increase the bandwidth utilization. Time- and wavelength-domain reuse in the OTSI significantly saves optical components and red- uces blocking probability.

Quantitative Analysis on Postponement Strategies of Decoupling Points in Mass Customization

The key to mass customizing effectively is postponing the deco upling point of customer order in the supply network. This paper focused on quantitative analysis on postponement strategies of multiple decoupling points in mass customization to improve operating efficiency and quickly meet customer demands with a minimum amount of inventory.

Intrusion Detection for Wireless Mesh Networks using Finite State Machine

Wireless Mesh Networks is vulnerable to attacks due to the open medium, dynamically changing network topology, cooperative algorithms, Lack of centralized monitoring and management point. The traditional way of protecting networks with firewalls and encryption software is no longer suffi- cient and effective for those features. In this paper, we propose a distributed intrusion detection ap- proach based on timed automata. A cluster-based detection scheme is presented, where periodically a node is elected as the monitor node for a cluster. These monitor nodes can not only make local intrusion detection decisions, but also cooperatively take part in global intrusion detection. And then we con- struct the Finite State Machine （FSM） by the way of manually abstracting the correct behaviors of the node according to the routing protocol of Dynamic Source Routing （DSR）. The monitor nodes can verify every node＇s behavior by the Finite State Ma- chine （FSM）, and validly detect real-time attacks without signatures of intrusion or trained data.Compared with the architecture where each node is its own IDS agent, our approach is much more efficient while maintaining the same level of effectiveness. Finally, we evaluate the intrusion detection method through simulation experiments.