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 中国物理 B , 2010, Abstract: This paper proposes a novel approach for fault diagnosis of a time-delay complex dynamical network. Unlike the other methods, assuming that the dynamics of the network can be described by a linear stochastic model, or using the state variables of nodes in the network to design an adaptive observer, it only uses the output variable of the nodes to design an observer and an adaptive law of topology matrix in the observer of a complex network, leading to simple design of the observer and easy realisation of topology monitoring for the complex networks in real engineering. The proposed scheme can monitor any changes of the topology structure of a time-delay complex network. The effectiveness of this method is successfully demonstrated by virtue of a complex networks with Lorenz model.
 Computer Science , 2013, Abstract: The robustness and integrity of IP networks require efficient tools for traffic monitoring and analysis, which scale well with traffic volume and network size. We address the problem of optimal large-scale flow monitoring of computer networks under resource constraints. We propose a stochastic optimization framework where traffic measurements are done by exploiting the spatial (across network links) and temporal relationship of traffic flows. Specifically, given the network topology, the state-space characterization of network flows and sampling constraints at each monitoring station, we seek an optimal packet sampling strategy that yields the best traffic volume estimation for all flows of the network. The optimal sampling design is the result of a concave minimization problem; then, Kalman filtering is employed to yield a sequence of traffic estimates for each network flow. We evaluate our algorithm using real-world Internet2 data.
 Journal of Water Resource and Protection (JWARP) , 2016, DOI: 10.4236/jwarp.2016.81005 Abstract: In abandoned mine sites, i.e., mine sites where mining operations have ended, wide spread contaminations are often evident, but the potential sources and pathways of contamination especially through the subsurface, are difficult to identify due to inadequate and sparse geochemical measurements available. Therefore, it is essential to design and implement a planned monitoring net-work to obtain essential information required for establishing the potential contamination source locations, i.e., waste dumps, tailing dams, pits and possible pathways through the subsurface, and to design a remediation strategy for rehabilitation. This study presents an illustrative application of modeling the flow and transport processes and monitoring network design in a study area hydrogeologically resembling an abandoned mine site in Queensland, Australia. In this preliminary study, the contaminant transport process modeled does not incorporate the reactive geochemistry of the contaminants. The transport process is modeled considering a generic conservative contaminant for the illustrative purpose of showing the potential application of an optimal monitoring design methodology. This study aims to design optimal monitoring network to: 1) minimize the contaminant solute mass estimation error; 2) locate the plume boundary; 3) select the monitoring locations with (potentially) high concentrations. A linked simulation optimization based methodology is utilized for optimal monitoring network design. The methodology is applied utilizing a recently developed software package CARE-GWMND, developed at James Cook University for optimal monitoring network design. Given the complexity of the groundwater systems and the sparsity of pollutant concentration observation data from the field, this software is capable of simulating the groundwater flow and solute transport with spatial interpolation of data from a sparse set of available data, and it utilizes the optimization algorithm to determine optimum locations for implementing monitoring wells.
 Journal of Environmental Protection (JEP) , 2013, DOI: 10.4236/jep.2013.45A004 Abstract: The groundwater system is often polluted by different sources of contamination where the sources are difficult to detect. The presence of contamination in groundwater poses significant challenges to its delineation and quantification. The remediation of a contaminated site requires an optimal decision making system to identify the pollutant source characteristics accurately and efficiently. The source characteristics are generally identified using contaminant concentration measurements from arbitrary or planned monitoring locations. To effectively characterize the sources of pollution, the monitoring locations should be selected appropriately. An efficient monitoring network will result in satisfactory characterization of contaminant sources. On the other hand, an appropriate design of monitoring network requires reliable source characteristics. A coupled iterative sequential source identification and dynamic monitoring network design, improves substantially the accuracy of source identification model. This paper reviews different source identification and monitoring network design methods in groundwater contaminant sites. Further, the models for sequential integration of these two models are presented. The effective integration of source identification and dedicated monitoring network design models, distributed sources, parameter uncertainty, and pollutant geo-chemistry are some of the issues which need to be addressed in efficient, accurate and widely applicable methodologies for identification of unknown pollutant sources in contaminated aquifers.
 Journal of Networks , 2012, DOI: 10.4304/jnw.7.5.838-844 Abstract: In view of the characteristics of greenhouse environment monitoring system, a system scheme based on wireless sensor network (WSN) is presented, which adopts Atmega128L chip and CC2530 that is a low power RF chip from TI to design the sink node and sensor nodes in the WSN. The monitoring and management center can control the temperature and humidity of the greenhouse, measure the carbon dioxide content, and collect the information about intensity of illumination, and so on. And the system adopts multilevel energy memory. It combines energy management with energy transfer, which makes the energy collected by solar energy batteries be used reasonably. Therefore, the self-managing energy supply system is established. In addition, the nodes deployment method and time synchronization problem are analyzed in detail. The system can solve the problem of complex cabling with the advantages of low power consumption, low cost, good robustness, extended flexible and high reliability. An effective tool is provided for monitoring and analysis decision-making of the greenhouse environment.
 Latin American applied research , 2006, Abstract: an air-quality monitoring network properly designed is a key component of any air quality control programme. this paper presents an objective procedure to determine the minimum number of monitoring sites needed to detect the occurrence of background air pollutant concentrations greater than a reference concentration level (cl) in an urban area. we propose an air quality monitoring network design based on the analysis of the results of atmospheric dispersion models, in order to identify the grid cells (in which the city is divided) where the air pollutant concentration exceeds cl. at present, buenos aires city has not an air quality monitoring network. this paper also describes the application of the proposed methodology to design a monitoring network to control pm10 levels in buenos aires. results show that four monitoring stations are required to detect the occurrence of pm10 24h-concentrations greater than cl=0.150 mg m-3.
 Latin American applied research , 2006, Abstract: An air-quality monitoring network properly designed is a key component of any air quality control programme. This paper presents an objective procedure to determine the minimum number of monitoring sites needed to detect the occurrence of background air pollutant concentrations greater than a reference concentration level (C L) in an urban area. We propose an air quality monitoring network design based on the analysis of the results of atmospheric dispersion models, in order to identify the grid cells (in which the city is divided) where the air pollutant concentration exceeds C L. At present, Buenos Aires city has not an air quality monitoring network. This paper also describes the application of the proposed methodology to design a monitoring network to control PM10 levels in Buenos Aires. Results show that four monitoring stations are required to detect the occurrence of PM10 24h-concentrations greater than C L=0.150 mg m-3.
 International Journal of Distributed Sensor Networks , 2009, DOI: 10.1080/15501320701343869 Abstract: In this work we present the design of jWebDust, a software environment for monitoring and controlling sensor networks via a web interface. Our software architecture provides a range of services that allow to create customized applications with minimum implementation effort that are easy to administrate. We present its open architecture, the most important design decisions, and discuss its distinct features and functionalities. jWebDust will allow heterogeneous components to operate in the same sensor network, and the integrated management and control of multiple such networks by defining web-based mechanisms to visualize the network state, the results of queries, and a means to inject queries in the network.
 Computer Science , 2012, Abstract: For a closed-loop system, which has a contention-based multiple access network on its sensor link, the Medium Access Controller (MAC) may discard some packets when the traffic on the link is high. We use a local state-based scheduler to select a few critical data packets to send to the MAC. In this paper, we analyze the impact of such a scheduler on the closed-loop system in the presence of traffic, and show that there is a dual effect with state-based scheduling. In general, this makes the optimal scheduler and controller hard to find. However, by removing past controls from the scheduling criterion, we find that certainty equivalence holds. This condition is related to the classical result of Bar-Shalom and Tse, and it leads to the design of a scheduler with a certainty equivalent controller. This design, however, does not result in an equivalent system to the original problem, in the sense of Witsenhausen. Computing the estimate is difficult, but can be simplified by introducing a symmetry constraint on the scheduler. Based on these findings, we propose a dual predictor architecture for the closed-loop system, which ensures separation between scheduler, observer and controller. We present an example of this architecture, which illustrates a network-aware event-triggering mechanism.
 Physics , 2007, DOI: 10.1088/1367-2630/10/1/013028 Abstract: We apply complex network analysis to the state spaces of random Boolean networks (RBNs). An RBN contains $N$ Boolean elements each with $K$ inputs. A directed state space network (SSN) is constructed by linking each dynamical state, represented as a node, to its temporal successor. We study the heterogeneity of an SSN at both local and global scales, as well as sample-to-sample fluctuations within an ensemble of SSNs. We use in-degrees of nodes as a local topological measure, and the path diversity [Phys. Rev. Lett. 98, 198701 (2007)] of an SSN as a global topological measure. RBNs with $2 \leq K \leq 5$ exhibit non-trivial fluctuations at both local and global scales, while K=2 exhibits the largest sample-to-sample, possibly non-self-averaging, fluctuations. We interpret the observed multi scale'' fluctuations in the SSNs as indicative of the criticality and complexity of K=2 RBNs. Garden of Eden'' (GoE) states are nodes on an SSN that have in-degree zero. While in-degrees of non-GoE nodes for $K>1$ SSNs can assume any integer value between 0 and $2^N$, for K=1 all the non-GoE nodes in an SSN have the same in-degree which is always a power of two.
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