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A distributed architecture for efficient parallelization and computation of knowledge-based temporal abstractions

JOURNAL OF INTELLIGENT INFORMATION SYSTEMS 2012年第1期39卷 249-286页

作者： Shabtai, Asaf Shahar, Yuval Elovici, Yuval Ben Gurion Univ Negev Dept Informat Syst Engn IL-84105 Beer Sheva Israel Ben Gurion Univ Negev Deutsch Telekom Labs IL-84105 Beer Sheva Israel

Today, data storage capabilities as well as computational power are rapidly increasing. On the one hand, this improvement makes it possible to generate and store a great amount of temporal (time-oriented) data for future query, analysis and discovery of new knowledge. On the other hand, systems and experts are encountering new problems in processing this increased amount of data. The rapid growth in stored time-oriented data necessitates the development of new methods for handling, processing, and interpreting large amounts of temporal data. One approach is to use an automatic summarization process based on predefined knowledge, such the Knowledge-Based Temporal-Abstraction (KBTA) method. This method enables one to summarize and reduce the amount of raw data by creating higher level interpretations based on predefined domain knowledge. Unfortunately, the task of temporal abstraction is inherently computationally expensive, especially when an enormous volume of multivariate data has to be handled and when complex patterns need to be considered. In this research, we address the scalability problem of a temporal-abstraction task that involves processing significantly large amounts of raw data. We propose a new computational framework, the distributed KBTA (DKBTA), which efficiently distributes the abstraction process among several parallel computational nodes, in order to achieve an acceptable computation time. The DKBTA framework distributes the temporal-abstraction process along one or more computational axes, each of which enables parallelization of one or more temporal-abstraction tasks into which the main temporal-abstraction task is decomposed, such as by different subject groups, concepts types, or abstraction types. We have implemented the DKBTA framework and have evaluated it in a preliminary fashion in the medical and the information security domains, with encouraging results. In our small-scale evaluation, only distribution along the subjects axis and someti

关键词： Temporal reasoning Knowledge-based systems Temporal-abstraction distributed computation Parallel computation Temporal data mining

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PageRank computation via a distributed randomized approach with lossy communication

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SYSTEMS & CONTROL LETTERS 2012年第12期61卷 1221-1228页

作者： Ishii, Hideaki Tempo, Roberto Bai, Er-Wei Tokyo Inst Technol Dept Computat Intelligence & Syst Sci Midori Ku Yokohama Kanagawa 2268502 Japan Politecn Torino CNR IEIIT I-10129 Turin Italy Univ Iowa Dept Elect & Comp Engn Seamans Ctr Engn Arts & Sci 4316 Iowa City IA 52242 USA Queens Univ Belfast Sch Elect Elect Engn & Comp Sci Belfast BT7 1NN Antrim North Ireland

For ranking web pages in search results, Google employs the so-called PageRank algorithm, which provides a measure of importance to each page based on the web structure. Recently, we have developed a distributed randomized approach for this algorithm, where pages compute their own PageRank by communicating over selected links. In this paper, the focus is on the effects of unreliability in communication channels. Specifically, we consider random data losses modeled as a Markov chain and introduce a generalized version of the distributed scheme. Its convergence properties and the error in the approximated PageRank are analyzed. (C) 2012 Elsevier B.V. All rights reserved.

关键词： distributed computation Multi-agent consensus PageRank algorithm Randomization Search engines Stochastic matrices

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The Optimization Methods Based on Big Data Technologies of Power System Protection

The Optimization Methods Based on Big Data Technologies of P...

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2014 3rd International Conference on Micro Nano Devices,Structure and Computing Systems(MNDSCS 2014)

作者： Haoran Xue Bin Li Kun Ji Zhiqiang Wang Xiaojun Kong NARI Group Corporation(State Grid Electric Power Research Institute)

Power system protection is one important work which relate to security and stability of the power system. Power system relay protection is a very important part of power system and it relates to the power system security and stability. The time for fault reaction of power system protection determines the reliability of system protection and sensitivity. This paper mainly for the malfunctions of power system, we used the techniques of big data to reduce the size of the power network. We used the distributed computation and parallel computing to calculate fault calculation, topology analysis and setting calculation, which can shorten the operation time of protection equipment. At the same time, it also can improve the quality of the power and it can reduce the time harming the equipment and ensure the stable operation of the system.

关键词： Power system relay protection Technologies of big data distributed computation Parallel computation Failure computational analysis

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The Study of Power System Protection Based on Big Data Technologies

The Study of Power System Protection Based on Big Data Techn...

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2014 International Conference on Information Technology and Management Engineering(ITME 2014)

作者： Jia WU Dan SU Ling-feng XU Shun WU Zheng-pu NIE JiBei Electric Power Corporation

Power system protection is a very important work related to security and stability of the power system. Power system relay protection is a main part of power system. The time for fault reaction of power system protection determines the reliability and sensitivity. This paper mainly for the malfunctions of power system, techniques of big data is used to reduce the size of the power network. distributed computation and parallel computing is used in fault calculation, topology analysis and setting calculation, which can shorten the operation time of protection equipment. It also can improve the quality of the power and ensure the stable operation of the system.

关键词： Power system relay protection Technologies of big data distributed computation Parallel computation Failure computational analysis

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computation over Mismatched Channels

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IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS 2013年第4期31卷 666-677页

作者： Karamchandani, Nikhil Niesen, Urs Diggavi, Suhas Univ Calif Los Angeles Dept Elect Engn Los Angeles CA 90095 USA Univ Calif San Diego Informat Theory & Applicat Ctr La Jolla CA 92093 USA Alcatel Lucent Bell Labs Murray Hill NJ 07974 USA

We consider the problem of distributed computation of a target function over a two-user deterministic multiple-access channel. If the target and channel functions are matched (i.e., compute the same function), significant performance gains can be obtained by jointly designing the communication and computation tasks. However, in most situations there is mismatch between these two functions. In this work, we analyze the impact of this mismatch on the performance gains achievable with joint communication and computation designs over separation-based designs. We show that for most pairs of target and channel functions there is no such gain, and separation of communication and computation is optimal.

关键词： distributed computation multiple access information theory separation theorem

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Anonymization of Centralized and distributed Social Networks by Sequential Clustering

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IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING 2013年第2期25卷 311-324页

作者： Tassa, Tamir Cohen, Dror J. Open Univ Dept Math & Comp Sci IL-43537 Raanana Israel

We study the problem of privacy-preservation in social networks. We consider the distributed setting in which the network data is split between several data holders. The goal is to arrive at an anonymized view of the unified network without revealing to any of the data holders information about links between nodes that are controlled by other data holders. To that end, we start with the centralized setting and offer two variants of an anonymization algorithm which is based on sequential clustering (Sq). Our algorithms significantly outperform the SaNGreeA algorithm due to Campan and Truta which is the leading algorithm for achieving anonymity in networks by means of clustering. We then devise secure distributed versions of our algorithms. To the best of our knowledge, this is the first study of privacy preservation in distributed social networks. We conclude by outlining future research proposals in that direction.

关键词： Social networks clustering privacy preserving data mining distributed computation

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Robust Analog Function computation via Wireless Multiple-Access Channels

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IEEE TRANSACTIONS ON COMMUNICATIONS 2013年第9期61卷 3863-3877页

作者： Goldenbaum, Mario Stanczak, Slawomir Tech Univ Berlin Fachgebiet Informat Theorie & Theoret Informat Te Berlin Germany Tech Univ Munich Lehrstuhl Theoret Informat Tech D-80290 Munich Germany Heinrich Hertz Inst Nachrichtentech Berlin GmbH Fraunhofer Inst Telecommun Berlin Germany

Wireless sensor network applications often involve the computation of pre-defined functions of the measurements such as for example the arithmetic mean or maximum value. Standard approaches to this problem separate communication from computation: digitized sensor readings are transmitted interference-free to a fusion center that reconstructs each sensor reading and subsequently computes the sought function value. Such separation-based computation schemes are generally highly inefficient as a complete reconstruction of individual sensor readings at the fusion center is not necessary to compute a function of them. In particular, if the mathematical structure of the channel is suitably matched (in some sense) to the function of interest, then channel collisions induced by concurrent transmissions of different nodes can be beneficially exploited for computation purposes. This paper proposes an analog computation scheme that allows for an efficient estimate of linear and nonlinear functions over the wireless multiple-access channel. A match between the channel and the function being evaluated is thereby achieved via some pre-processing on the sensor readings and post-processing on the superimposed signals observed by the fusion center. After analyzing the estimation error for two function examples, simulations are presented to show the potential for huge performance gains over time-and code-division multiple-access based computation schemes.

关键词： computation over multiple-access channels in-network processing function estimation distributed computation wireless sensor networks

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Entrusting Private computation and Data to Untrusted Networks

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IEEE TRANSACTIONS ON DEPENDABLE AND SECURE COMPUTING 2013年第4期10卷 225-238页

作者： Brun, Yuriy Medvidovic, Nenad Univ Massachusetts Sch Comp Sci Amherst MA 01003 USA Univ So Calif Dept Comp Sci Henry Salvatori Comp Sci Ctr 338 Los Angeles CA 90089 USA

We present sTile, a technique for distributing trust-needing computation onto insecure networks, while providing probabilistic guarantees that malicious agents that compromise parts of the network cannot learn private data. With sTile, we explore the fundamental cost of achieving privacy through data distribution and bound how much less efficient a privacy-preserving system is than a nonprivate one. This paper focuses specifically on NP-complete problems and demonstrates how sTile-based systems can solve important real-world problems, such as protein folding, image recognition, and resource allocation. We present the algorithms involved in sTile and formally prove that sTile-based systems preserve privacy. We develop a reference sTile-based implementation and empirically evaluate it on several physical networks of varying sizes, including the globally distributed PlanetLab testbed. Our analysis demonstrates sTile's scalability and ability to handle varying network delay, as well as verifies that problems requiring privacy-preservation can be solved using sTile orders of magnitude faster than using today's state-of-the-art alternatives.

关键词： Privacy trusted computing untrusted networks distributed computation PlanetLab sTile tile assembly model

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distributed PageRank computation with Link Failures

Distributed PageRank Computation with Link Failures

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American Control Conference 2009

作者： Ishii, Hideaki Tempo, Roberto Tokyo Inst Technol Dept Computat Intelligence & Syst Sci Midori Ku 4259-J2-54Nagatsuta Cho Yokohama Kanagawa 2268502 Japan Politecn Torino CNR IEIIT I-10129 Turin Italy

ISBN: (纸本)9781424445233

The Google search engine employs the so-called PageRank algorithm for ranking the search results. This algorithm quantifies the importance of each web page based on the link structure of the web. In this paper, we continue our recent work on distributed randomized computation of PageRank, where the pages locally determine their values by communicating with linked pages. In particular, we propose a distributed randomized algorithm with limited information, where only part of the linked pages is required to be contacted. This is useful to enhance flexibility and robustness in computation and communication.

关键词： distributed computation Link failures Multiagent consensus PageRank algorithm Randomization Stochastic matrices

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On the distributed Binary Consensus Algorithm in Wireless Sensor Networks

On the Distributed Binary Consensus Algorithm in Wireless Se...

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7th International Conference on Signal Processing and Communication Systems (ICSPCS)

作者： Abderrazak, Abdaoui El Fouly, Tarek Mohamed Qatar Univ Dept Comp Sci POB 2713 Doha Qatar

ISBN: (纸本)9781479913190

We consider the binary consensus problem over the wireless sensor networks (WSN), where each node of the network initially observes one of two states and the aim of each node is to decide which one of the two states was held by the majority of nodes. In this paper we consider the averaging of a measurement in a WSN composed of N nodes. We evaluate the distributed binary consensus algorithm by deriving the average convergence time of the algorithm. Since this time has been evaluated theoretically for mathematical aspects [1], we complete this work by considering real life environment including packet loss phenomenon and automatic repeat request (ARQ) protocol used in real message transmissions. In addition we compare the new analytical results with those obtained by a hardware emulation of the same binary consensus algorithm under TinyOS and TOSSIM. In performance evaluation, we consider the analysis of the average convergence time for node states. In the simulations, we apply the distributed binary consensus algorithm for fully connected, ring, path, Erdos Reny random, and star-shaped topologies.

关键词： Binary consensus algorithm distributed computation TinyOS IRIS Motes Tossim Wireless sensor network ARQ packet loss

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