8,932 research outputs found

    When Both Transmitting and Receiving Energies Matter: An Application of Network Coding in Wireless Body Area Networks

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    A network coding scheme for practical implementations of wireless body area networks is presented, with the objective of providing reliability under low-energy constraints. We propose a simple network layer protocol for star networks, adapting redundancy based on both transmission and reception energies for data and control packets, as well as channel conditions. Our numerical results show that even for small networks, the amount of energy reduction achievable can range from 29% to 87%, as the receiving energy per control packet increases from equal to much larger than the transmitting energy per data packet. The achievable gains increase as a) more nodes are added to the network, and/or b) the channels seen by different sensor nodes become more asymmetric.Comment: 10 pages, 7 figures, submitted to the NC-Pro Workshop at IFIP Networking Conference 2011, and to appear in the conference proceedings, published by Springer-Verlag, in the Lecture Notes in Computer Science (LNCS) serie

    SRAT-Distribution Voltage Sags and Reliability Assessment Tool

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    Interruptions to supply and sags of distribution system voltage are the main aspects causing customer complaints. There is a need for analysis of supply reliability and voltage sag to relate system performance with network structure and equipment design parameters. This analysis can also give prediction of voltage dips, as well as relating traditional reliability and momentary outage measures to the properties of protection systems and to network impedances. Existing reliability analysis software often requires substantial training, lacks automated facilities, and suffers from data availability. Thus it requires time-consuming manual intervention for the study of large networks. A user-friendly sag and reliability assessment tool (SRAT) has been developed based on existing impedance data, protection characteristics, and a model of failure probability. The new features included in SRAT are a) efficient reliability and sag assessments for a radial network with limited loops, b) reliability evaluation associated with realistic protection and restoration schemes, c) inclusion of momentary outages in the same model as permanent outage evaluation, d) evaluation of the sag transfer through meshed subtransmission network, and e) simplified probability distribution model determined from available faults records. Examples of the application of the tools to an Australian distribution network are used to illustrate the application of this model

    Investigating Performance and Reliability of Process Bus Networks for Digital Protective Relaying

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    To reduce the cost of complex and long copper wiring, as well as to achieve flexibility in signal communications, IEC 61850 part 9-2 proposes a process bus communication network between process level switchyard equipments, and bay level protection and control (P&C) Intelligent Electronic Devices (IEDs). After successful implementation of Ethernet networks for IEC 61850 standard part 8-1 (station bus) at several substations worldwide, major manufacturers are currently working on the development of interoperable products for the IEC 61850-9-2 based process bus. The major technical challenges for applying Ethernet networks at process level include: 1) the performance of time critical messages for protection applications; 2) impacts of process bus Ethernet networks on the reliability of substation protection systems. This work starts with the performance analysis in terms of time critical Sampled Value (SV) messages loss and/or delay over the IEC 61850-9-2 process bus networks of a typical substation. Unlike GOOSE, the SV message is not repeated several times, and therefore, there is no assurance that each SV message will be received from the process bus network at protection IEDs. Therefore, the detailed modeling of IEC 61850 based substation protection devices, communication protocols, and packet format is carried out using an industry-trusted simulation tool OPNET, to study and quantify number of SV loss and delay over the process bus. The impact of SV loss/delay on digital substation protection systems is evident, and recognized by several manufacturers. Therefore, a sample value estimation algorithm is developed in order to enhance the performance of digital substation protection functions by estimating the lost and delayed sampled values. The error of estimation is evaluated in detail considering several scenarios of power system relaying. The work is further carried out to investigate the possible impact of SV loss/delay on protection functions, and test the proposed SV estimation algorithm using the hardware setup. Therefore, a state-of-the-art process bus laboratory with the protection IEDs and merging unit playback simulator using industrial computers on the QNX hard-real-time platform, is developed for a typical IEC 61850-9-2 based process bus network. Moreover, the proposed SV estimation algorithm is implemented as a part of bus differential and transmission line distance protection IEDs, and it is tested using the developed experimental setup for various SV loss/delay scenarios and power system fault conditions. In addition to the performance analysis, this work also focuses on the reliability aspects of protection systems with process bus communication network. To study the impact of process bus communication on reliability indices of a substation protection function, the detailed reliability modeling and analysis is carried out for a typical substation layout. First of all, reliability analysis is done using Reliability Block Diagrams (RBD) considering various practical process bus architectures, as well as, time synchronization techniques. After obtaining important failure rates from the RBD, an extended Markov model is proposed to analyze the reliability indices of protection systems, such as, protection unavailability, abnormal unavailability, and loss of security. It is shown with the proposed Markov model that the implementation of sampled value estimation improves the reliability indices of a protection system

    Investigation of the robustness of star graph networks

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    The star interconnection network has been known as an attractive alternative to n-cube for interconnecting a large number of processors. It possesses many nice properties, such as vertex/edge symmetry, recursiveness, sublogarithmic degree and diameter, and maximal fault tolerance, which are all desirable when building an interconnection topology for a parallel and distributed system. Investigation of the robustness of the star network architecture is essential since the star network has the potential of use in critical applications. In this study, three different reliability measures are proposed to investigate the robustness of the star network. First, a constrained two-terminal reliability measure referred to as Distance Reliability (DR) between the source node u and the destination node I with the shortest distance, in an n-dimensional star network, Sn, is introduced to assess the robustness of the star network. A combinatorial analysis on DR especially for u having a single cycle is performed under different failure models (node, link, combined node/link failure). Lower bounds on the special case of the DR: antipode reliability, are derived, compared with n-cube, and shown to be more fault-tolerant than n-cube. The degradation of a container in a Sn having at least one operational optimal path between u and I is also examined to measure the system effectiveness in the presence of failures under different failure models. The values of MTTF to each transition state are calculated and compared with similar size containers in n-cube. Meanwhile, an upper bound under the probability fault model and an approximation under the fixed partitioning approach on the ( n-1)-star reliability are derived, and proved to be similarly accurate and close to the simulations results. Conservative comparisons between similar size star networks and n-cubes show that the star network is more robust than n-cube in terms of ( n-1)-network reliability

    A hybrid algorithm for Bayesian network structure learning with application to multi-label learning

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    We present a novel hybrid algorithm for Bayesian network structure learning, called H2PC. It first reconstructs the skeleton of a Bayesian network and then performs a Bayesian-scoring greedy hill-climbing search to orient the edges. The algorithm is based on divide-and-conquer constraint-based subroutines to learn the local structure around a target variable. We conduct two series of experimental comparisons of H2PC against Max-Min Hill-Climbing (MMHC), which is currently the most powerful state-of-the-art algorithm for Bayesian network structure learning. First, we use eight well-known Bayesian network benchmarks with various data sizes to assess the quality of the learned structure returned by the algorithms. Our extensive experiments show that H2PC outperforms MMHC in terms of goodness of fit to new data and quality of the network structure with respect to the true dependence structure of the data. Second, we investigate H2PC's ability to solve the multi-label learning problem. We provide theoretical results to characterize and identify graphically the so-called minimal label powersets that appear as irreducible factors in the joint distribution under the faithfulness condition. The multi-label learning problem is then decomposed into a series of multi-class classification problems, where each multi-class variable encodes a label powerset. H2PC is shown to compare favorably to MMHC in terms of global classification accuracy over ten multi-label data sets covering different application domains. Overall, our experiments support the conclusions that local structural learning with H2PC in the form of local neighborhood induction is a theoretically well-motivated and empirically effective learning framework that is well suited to multi-label learning. The source code (in R) of H2PC as well as all data sets used for the empirical tests are publicly available.Comment: arXiv admin note: text overlap with arXiv:1101.5184 by other author
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