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Model Based Peer-to-Peer Estimator over Wireless Sensor Networks *

IFAC Proceedings Volumes 2012年第26期45卷 19-24页

作者： Yuzhe Xu Carlo Fischione Alberto Speranzon ACCESS Linnaeus Center Electrical Engineering KTH Royal Institute of Technology 100-44 Stockholm Sweden United Technologies Research Center East Hartford CT USA

A peer-to-peer estimator computes local estimates at each node by combining the information from neighboring nodes without the need of central coordination. Although more flexible and scalable, peer-to-peer minimum variance estimators are difficult to design because of message losses and lack of network coordination. In this paper, we propose a new peer-to-peer estimator that allows to recover a time-varying scalar signal from measurements corrupted by an unknown non-zero mean independent noise or disturbances. Message losses occurring over the network and absence of central coordination are considered. Novel theoretical solutions are developed by taking advantage of a model of the signal dynamics. The proposed approach simultaneously guarantees a bounded mean value and minimum variance of the estimation error. Simulation results illustrate the performance of the proposed method.

关键词： distributed estimation Fast-Lipschitz Optimization Wireless Sensor Networks Parallel distributed computation

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distributed Analytics for Steady State Operation of Autonomous Microgrids

Distributed Analytics for Steady State Operation of Autonomo...

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IEEE Power and Energy Society General Meeting

作者： Joydeep Mitra Niannian Cai Department of Electrical & Computer Engineering Michigan State University East Lansing MI 48824 USA

ISBN: (纸本)9781467327275

It has often been argued that microgrids that predominantly contain customer-owned generation (co-gen) should have autonomous control, i.e., their operation, even in gridconnected mode, should not be controlled by the utility providing the point of common coupling (PCC). Some of the control strategies proposed in recent literature rely on distributed control platforms, such as multi-agent systems (MAS). The analytics, i.e., computational and decision-making processes, that occur on these distributed computation platforms are fundamentally different from those that are performed in traditional control centers. This is due partly to the difference in the computation platforms and partly to the fact that microgrids are dynamic in configuration. This paper describes current research in the application of graph-theoretic and distributed computation concepts toward the development of analytics, such as load balancing and optimal operation, that can be implemented on a distributed platform, for the steady state operation of microgrids.

关键词： microgrid analytics autonomous control diakoptics distributed computation multi-agent systems. stability operations MICRO-GRID Platform Distribute Control centres point of common coupling autonomous control Multi-agent systems arithmetic Optimal operation Load balancing

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distributed Randomized Algorithms for the PageRank computation

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IEEE TRANSACTIONS ON AUTOMATIC CONTROL 2010年第9期55卷 1987-2002页

作者： Ishii, Hideaki Tempo, Roberto Tokyo Inst Technol Dept Computat Intelligence & Syst Sci Yokohama Kanagawa 2268502 Japan Politecn Torino IEIIT CNR I-10129 Turin Italy

In the search engine of Google, the PageRank algorithm plays a crucial role in ranking the search results. The algorithm quantifies the importance of each web page based on the link structure of the web. We first provide an overview of the original problem setup. Then, we propose several distributed randomized schemes for the computation of the PageRank, where the pages can locally update their values by communicating to those connected by links. The main objective of the paper is to show that these schemes asymptotically converge in the mean-square sense to the true PageRank values. A detailed discussion on the close relations to the multi-agent consensus problems is also given.

关键词： distributed computation multi-agent consensus PageRank algorithm randomization search engines stochastic matrices

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distributed averaging on digital erasure networks

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AUTOMATICA 2011年第1期47卷 115-121页

作者： Carli, Ruggero Como, Giacomo Frasca, Paolo Garin, Federica Politecn Torino Dipartimento Matemat Turin Italy Univ Padua Dept Informat Engn Padua Italy MIT Informat & Decis Syst Lab Cambridge MA 02139 USA INRIA Rhone Alpes NeCS Team Grenoble France

Iterative distributed algorithms are studied for computing arithmetic averages over networks of agents connected through memoryless broadcast erasure channels. These algorithms do not require the agents to have any knowledge about the global network structure or size. Almost sure convergence to state agreement is proved, and the communication and computational complexities of the algorithms are analyzed. Both the number of transmissions and the number of computations performed by each agent of the network are shown to grow not faster than poly-logarithmically in the desired precision. The impact of the graph topology on the algorithms performance is analyzed as well. Moreover, it is shown how, in the presence of noiseless communication feedback, one can modify the algorithms, significantly improving their performance versus complexity trade-off. (C) 2010 Elsevier Ltd. All rights reserved.

关键词： distributed computation distributed control Digital communications Control with communication constraints Average consensus

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Stream engines meet wireless sensor networks: cost-based planning and processing of complex queries in AnduIN

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distributed AND PARALLEL DATABASES 2011年第1-2期29卷 151-183页

作者： Klan, Daniel Karnstedt, Marcel Hose, Katja Ribe-Baumann, Liz Sattler, Kai-Uwe Ilmenau Univ Technol Databases & Informat Syst Grp Ilmenau Germany Max Planck Inst Informat Saarbrucken Germany NUI Galway DERI Galway Ireland

Wireless sensor networks are powerful, distributed, self-organizing systems used for event and environmental monitoring. In-network query processors like TinyDB offer a user friendly SQL-like application development. Due to the sensor nodes' resource limitations, monolithic approaches often support only a restricted number of operators. For this reason, complex processing is typically outsourced to the base station. Nevertheless, previous work has shown that complete or partial in-network processing can be more efficient than the base station approach. In this paper, we introduce AnduIN, a system for developing, deploying, and running complex in-network processing tasks. In particular, we present the query planning and execution strategies used in AnduIN, a system combining sensor-local in-network processing and a data stream engine. Query planning employs a multi-dimensional cost model taking energy consumption into account and decides autonomously which query parts will be processed within the sensor network and which parts will be processed at the central instance.

关键词： Sensor networks Data streams Power awareness distributed computation In-network query processing Query planning

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Inferring Nonstationary Gene Networks from Longitudinal Gene Expression Microarrays

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JOURNAL OF SIGNAL PROCESSING SYSTEMS FOR SIGNAL IMAGE AND VIDEO TECHNOLOGY 2011年第2期65卷 261-273页

作者： Chang, Hsun-Hsien Ramoni, Marco F. Harvard Univ Sch Med Childrens Hosp Informat Program Harvard Mit Div Hlth Sci & Technol Boston MA 02115 USA

Inferring gene networks from longitudinal gene expression microarrays is a crucial step towards the study of gene regulatory mechanisms. A decade ago, expensive microarray technology restricted the number of samples undergoing gene expression profiling in single studies, leading the inference algorithms that assume stationary gene networks to the best solution. Thanks to decreasing cost of modern microarray technologies, more gene expression profiles can be assessed in single studies. With more samples available, we can relax the stationarity assumption and develop a method to infer dynamic gene networks, which can reflect more realistic biology where genes adaptively orchestrate each other. This paper applied the framework of dynamic Bayesian networks to infer adaptive gene interactions by identifying individual transition networks between pairs of consecutive times. Due to high computational burden of inferring the interconnection patterns among all genes over time, we designed a parallelizable inference algorithm to make feasible the task. We validated our approach by two clinical studies: yellow fever vaccination and mechanical periodontal therapy. The inferred dynamic networks achieved more than 90% predictive accuracy, a significant improvement when compared to stationary models (p<0.05). The adaptive models can help explain the induction of innate immunology in greater details after yellow fever vaccination and interpret the anti-inflammatory effect of mechanical periodontal therapy.

关键词： Nonstationary networks Bayesian networks distributed computation Gene expression

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Fastest distributed Consensus Problem on Fusion of Two Star Sensor Networks

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IEEE SENSORS JOURNAL 2011年第10期11卷 2494-2506页

作者： Jafarizadeh, Saber Jamalipour, Abbas Univ Sydney Sch Elect & Informat Engn Sydney NSW 2006 Australia

Finding optimal weights for the problem of fastest distributed consensus on sensor networks with different topologies has been an active area of research for a number of years. In this work, we present an analytical solution for the problem of Fastest distributed Consensus for a sensor network formed by fusing two different symmetric star sensor networks. In other words, a sensor network consisting of two different symmetric star sensor networks which are sharing the same central node. The solution procedure consists of stratification of associated connectivity graph of network and Semidefinite Programming ( SDP), particularly solving the slackness conditions. The optimal weights are obtained by inductive comparing of the characteristic polynomials initiated by slackness conditions. Some numerical simulations are carried out to investigate the tradeoff between the parameters of two fused star sensor networks, namely, the length and number of branches. Also, the obtained optimal weights has been compared with different weighting methods by evaluating the Second Largest Eigenvalue Modulus (SLEM) and comparing convergence time improvements numerically. Moreover, several examples of two fused star sensor networks with branches other than path graphs are introduced along with their optimal weights and SLEM.

关键词： distributed computation fastest distributed consensus semidefinite programming sensor networks

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distributed algorithmic mechanism design for scheduling on unrelated machines

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JOURNAL OF PARALLEL AND distributed COMPUTING 2011年第3期71卷 397-406页

作者： Carroll, Thomas E. Grosu, Daniel Wayne State Univ Dept Comp Sci Detroit MI 48202 USA Pacific NW Natl Lab Richland WA 99352 USA

In classical mechanism design the outcome of the mechanism is computed by a trusted central party. In this paper, we consider the design of distributed mechanisms in which the outcome is computed by the agents themselves. We propose distributed MinWork (DMW), a mechanism for solving the problem of scheduling on unrelated machines. We show that DMW is a faithful implementation of the MinWork mechanism, which was proposed by Nisan and Ronen in their seminal work (Nisan and Rouen (2001) [30]). We show that in addition to being faithful, DMW protects the anonymity of the losing agents and the privacy of their bids. Furthermore, we show that DMW is efficient as it has polynomial communication and computation costs. (C) 2010 Elsevier Inc. All rights reserved.

关键词： Algorithmic mechanism design Scheduling on unrelated machines Truthful mechanism distributed computation

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Information Dynamics in Small-World Boolean Networks

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ARTIFICIAL LIFE 2011年第4期17卷 293-314页

作者： Lizier, Joseph T. Pritam, Siddharth Prokopenko, Mikhail CSIRO Informat & Commun Technol Ctr N Ryde NSW 1670 Australia Max Planck Inst Math Sci D-04103 Leipzig Germany Univ Sydney Sch Informat Technol Sydney NSW 2006 Australia

Small-world networks have been one of the most influential concepts in complex systems science, partly due to their prevalence in naturally occurring networks. It is often suggested that this prevalence is due to an inherent capability to store and transfer information efficiently. We perform an ensemble investigation of the computational capabilities of small-world networks as compared to ordered and random topologies. To generate dynamic behavior for this experiment, we imbue the nodes in these networks with random Boolean functions. We find that the ordered phase of the dynamics (low activity in dynamics) and topologies with low randomness are dominated by information storage, while the chaotic phase (high activity in dynamics) and topologies with high randomness are dominated by information transfer. Information storage and information transfer are somewhat balanced (crossed over) near the small-world regime, providing quantitative evidence that small-world networks do indeed have a propensity to combine comparably large information storage and transfer capacity.

关键词： Random Boolean networks phase transitions small-world networks distributed computation information storage information transfer

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基于网格平台的电网故障诊断架构

基于网格平台的电网故障诊断架构

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中国电机工程学会电力系统自动化专业委员会2012年学术交流会

作者：王磊陈青高湛军李兆飞山东大学电网智能化调度与控制教育部重点实验室山东省济南市250061

故障诊断是未来智能电网可自愈的前提条件.为了进一步提高电网故障诊断系统的效率及准确性,文中提出了一种以数据网格为支撑,分布式系统为主体的新型电网故障诊断架构.数据网格能够为故障诊断系统提供及时、可靠的数据采集功能,而分布... 详细信息

故障诊断是未来智能电网可自愈的前提条件.为了进一步提高电网故障诊断系统的效率及准确性,文中提出了一种以数据网格为支撑,分布式系统为主体的新型电网故障诊断架构.数据网格能够为故障诊断系统提供及时、可靠的数据采集功能,而分布式系统提供的分布式计算技术能够极大地提高诊断程序的运行速度.两者的结合能够使这种新型的诊断系统在诊断速度及准确性上优于传统的客户/服务器(C/S)结构.最后,通过案例证明了新系统的可行性.

关键词： fault diagnosis data grid OGSA-DAI standard distributed computation

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