基于k-完美差异图的超节点拓扑结构构造

在超节点网络中,超节点拓扑结构及其动态维护和搜索路由机制,是影响网络性能和搜索效率的关键因素之一。在完美差异图(PDG)的基础上,提出了一种新的k-PDG结构,并利用该结构,建立了超节点网络——KPDGN,给出了KPDGN的动态维护和搜索路由机制。分析和模拟结果表明:KPDGN具有常数度数和固定邻接点特性,减少了查询所产生的带宽消耗,降低了拓扑构造和修复成本。

基于语义路由的P2P系统综述

介绍了P2P系统的发展状况,归纳了典型的结构化P2P系统模型,对结构化P2P系统中的节点拓扑结构、语义路由算法、数据存储和共享、应用层多播等热点问题进行了讨论,介绍了非结构化P2P系统的语义路由过程,总结了当前主要的基于语义路由P2P系统的优缺点,并据此提出了该领域的发展趋势。

中压配电网状态评估方法与实现流程

针对中压配电网特点,结合配电自动化SCADA系统基础量测数据及应用要求,通过建立量测节点拓扑结构模型和相应的实时状态矩阵计算与分析方法,提出了配电系统不良数据检测及校正的实现框架和流程,算例表明了该技术的正确性和可行性,符合目前配网在线监控应用实际要求。

Relay movement control for maintaining connectivity in aeronautical ad hoc networks

As a new sort of mobile ad hoc network(MANET), aeronautical ad hoc network(AANET) has fleet-moving airborne nodes(ANs) and suffers from frequent network partitioning due to the rapid-changing topology. In this work, the additional relay nodes(RNs) is employed to repair the network and maintain connectivity in AANET. As ANs move, RNs need to move as well in order to re-establish the topology as quickly as possible. The network model and problem definition are firstly given, and then an online approach for RNs' movement control is presented to make ANs achieve certain connectivity requirement during run time. By defining the minimum cost feasible moving matrix(MCFM), a fast algorithm is proposed for RNs' movement control problem. Simulations demonstrate that the proposed algorithm outperforms other control approaches in the highly-dynamic environment and is of great potential to be applied in AANET.

Analysis on Refinery System as a Complex Task-resource Network

Refinery system, a typical example of process systems, is presented as complex network in this paper. The topology of this system is described by task-resource network and modeled as directed and weighted graph, in which nodes represent various tasks and edges denote the resources exchanged among tasks. Using the properties of node degree distribution, strength distribution and other weighted quantities, we demonstrate the heterogeneity of the network and point out the relation between structural characters of vertices and the functionality of correspond- ing tasks. The above phenomena indicate that the design requirements and principles of production process contrib- ute to the heterogeneous features of the network. Besides, betweenness centrality of nodes can be used as an impor- tance indicator to provide additional information for decision making. The correlations between structure and weighted properties are investigated to further address the influence brought by production schemes in system con- nectivity patterns. Cascading failures model is employed to analyze the robustness of the network when targeted at- tack happens. Two capacity assignment strategies are compared in order to improve the robustness of the network at certain cost. The refinery system displays more reliable behavior when the protecting strategy considers heteroge- neous properties. This phenomenon further implies the structure-activity relationship of the refinery system and provides insightful suggestions for process system design. The results also indicate that robustness analysis is a _promising applicat!on of methodologies from complex networks to process system engineering..

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.

Distribution network planning algorithm based on Hopfield neural network

This paper presents a new algorithm based on Hopfield neural network to find the optimal solution for an electric distribution network. This algorithm transforms the distribution power network-planning problem into a directed graph-planning problem. The Hopfield neural network is designed to decide the in-degree of each node and is in combined application with an energy function. The new algorithm doesn’t need to code city streets and normalize data, so the program is easier to be realized. A case study applying the method to a district of 29 street proved that an optimal solution for the planning of such a power system could be obtained by only 26 iterations. The energy function and algorithm developed in this work have the following advantages over many existing algorithms for electric distribution network planning: fast convergence and unnecessary to code all possible lines.

ROBUSTNESS ANALYSIS OF LEADER-FOLLOWER CONSENSUS

In this paper,robustness properties of the leader-follower consensus are considered.Forsimplicity of presentation,the attention is focused on a group of continuous-time first-order dynamicagents with a time-invariant communication topology in the presence of communication errors.In orderto evaluate the robustness of leader-follower consensus,two robustness measures are proposed:the L_2gain of the error vector to the state of the network and the worst case L_2 gain at a node.Althoughthe L_2 gain of the error vector to the state of the network is widely used in robust control design andanalysis,the worst case L_2 gain at a node is less conservative with respect to the number of nodes inthe network.It is thus suggested that the worst case L_2 gain at a node is used when the robustnessof consensus is considered.Theoretical analysis and simulation results show that these two measuresare sensitive to the communication topology.In general,the 'optimal' communication topology thatcan achieve most robust performance with respect to either of the proposed robustness measures isdifficult to characterize and/or obtain.When the in-degree of each follower is one,it is shown thatboth measures reach a minimum when the leader can communicate to each node in the network.

EXPONENTIALLY ADAPTIVE SYNCHRONIZATION OF AN UNCERTAIN DELAYED DYNAMICAL NETWORK

Over the past decades, complex networks have been prosperous greatly in various fields of sciences and engineering. Much attention has been given to investigate the synchronization of complex networks in recent years. However, few work has done for the networks with uncertain parameters and unknown topology. In this paper, to further reveal the dynamical mechanism in complex networks with time delays, an uncertain general complex dynamical network with delayed nodes is studied. By constructing a drive network and a suitable slave network, several novel criteria for the networks consisting of the identical nodes and different nodes have been obtained based on the adaptive feedback method. Particularly, the hypotheses and the proposed adaptive laws for network synchronization are simple and can be readily applied in practical applications. Finally, numerical simulations are provided to illustrate the effectiveness of the proposed synchronization criteria.