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检索条件"主题词=Compression Algorithms"

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Compressing IP forwarding tables with fast and bounded update

Compressing IP forwarding tables with fast and bounded updat...

引用

International Workshop on Quality of Service

作者： Yuanyuan Zhang Mingwei Xu Fei Liang Ning Wang Penghan Chen Department of Computer Science and Technology Tsinghua University Beijing China Beijing University of Posts and Telecommunications Beijing China Institute for Communication Systems University of Surrey Guildford United Kingdom

The size of Forwarding Information Base (FIB) maintained at backbone routers is experiencing an exponential growth, and various solutions have been proposed in the literature. The main shortcoming of FIB compression is the update overhead. Only when the update speed of FIB compression algorithms is sufficiently fast and bounded, the probability of packet loss incurred by FIB compression operations during update can be completely avoided. However, no prior FIB compression algorithm can bound the worst case of update, and hence a mature solution with complete avoidance of packet loss is still yet to be identified. To address this issue, we propose the Unite and Split (US) compression algorithm to enable fast update with bounded worst case performance. Experimental results show that the average update speed of the US algorithm is almost the same as that of the binary trie without any compression.

关键词： compression algorithms IP networks Hardware Quality of service Packet loss Internet

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Novel Data compression Algorithm for Process Data

Novel Data Compression Algorithm for Process Data

引用

IEEE Conference on Control Applications (CCA)

作者： Purohit, Amit ABB Corp Res Ctr Control & Optimizat Grp Bangalore 560048 Karnataka India

ISBN: (纸本)9781479974092

Data compression algorithms are used in process plants to store and transmit data for analysis purposes. Amount of data is increasing in process plants due to advances in automation and process monitoring technologies. Process data historians are used in plants to store, manage, retrieve and analyze process data. Process data historians use data compression algorithms to effectively manage large amount of data. Best practiced compression algorithm in process data historians has a severe drawback that it significantly alters the statistical properties of reconstructed data;this results in incorrect analysis results which have financial and safety implications for the process plants. Proposed compression algorithm is designed to preserve the critical statistical properties for process data analysis which supports operational decision making in process plants. Case studies are presented on real plant data and simulated data to compare the performance of proposed algorithm with best practiced algorithm used in process data historians.

关键词： Accuracy Algorithm design and analysis compression algorithms Data compression Principal component analysis Redundancy Transforms compression algorithms Data compression Algorithm design and analysis Transform redundancy Process plants principal components analysis Historian plant data

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Applying Selectively Parallel I/O compression to Parallel Storage Systems 1

引用

20th European Conference on Parallel Computing (Euro-Par)

作者： Filgueira, Rosa Atkinson, Malcolm Tanimura, Yusuke Kojima, Isao Univ Edinburgh Sch Informat Edinburgh EH8 9AB Midlothian Scotland AIST Informat Technol Res Inst Tsukuba Ibaraki Japan

ISBN: (数字)9783319098739

ISBN: (纸本)9783319098739;9783319098722

This paper presents a new I/O technique called Selectively Parallel I/O compression (SPIOC) for providing high-speed storage and access to data in QoS enabled parallel storage systems. SPIOC reduces the time of I/O operations by applying transparent compression between the computing and the storage systems. SPIOC can predict whether to compress or not at runtime, allowing parallel or sequential compression techniques, guaranteeing QoS and allowing partial and full reading by decompressing the minimum part of the file. SPIOC maximises the measured efficiency of data movement by applying run-time customising compression before storing data in the Papio storage system.

关键词： Parallel File System Data Intensive Computing compression algorithms Adaptive systems

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Customizable compression architecture for efficient configuration in CGRAs 22

Customizable compression architecture for efficient configur...

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22nd IEEE Annual International Symposium on Field-Programmable Custom Computing Machines ((FCCM)

作者： Jafri, Syed M. A. H. Tajammul, Adeel Daneshtalab, Masoud Hemani, Ahmed Paul, Kolin Ellervee, Peeter Plosila, Juha Tenhunen, Hannu Turku Ctr Comp Sci Turku Finland Tallinn Univ Technol Tallinn Estonia Univ Turku Turku Finland Royal Inst Technol Stockholm Sweden Indian Inst Technol Delhi India

ISBN: (纸本)9781479951116

Today, Coarse Grained Reconfigurable Architectures (CGRAs) host multiple applications. Novel CGRAs allow each application to exploit runtime parallelism and time sharing. Although these features enhance the power and silicon efficiency, they significantly increase the configuration memory overheads. As a solution to this problem researchers have employed statistical compression, intermediate compact representation, and multicasting. Each of these techniques has different properties, and is therefore best suited for a particular class of applications. However, existing research only deals with these methods separately. In this paper we propose a morphable compression architecture that interleaves these techniques in a unique platform.

关键词： compression algorithms Computer architecture Educational institutions Hardware Multicast communication Silicon Software Coarse grained reconfigurable architectures compression configuration compression energy aware systems multicast communication compression algorithms Computer Architecture Educational institutions Computer hardware Silicon computer software compression Coarse-grained Reconfigurable Architecture time sharing

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On compressing massive streaming graphs with Quadtrees

On compressing massive streaming graphs with Quadtrees

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IEEE International Conference on Big Data

作者： Michael Nelson Sridhar Radhakrishnan Amlan Chatterjee Chandra N. Sekharan School of Computer Science University of Oklahoma Norman OK USA Department of Computer Science California State University Dominguez Hills Carson CA USA Department of Computer Science Loyola University Chicago Chicago IL USA

Social networks are constantly changing as new members join, existing members leave, and `followers' or `friends' are formed and disappear. The model that captures this constantly changing graph is the streaming graph model. Given a massive graph data stream wherein the number of nodes is in the order of millions and the number of edges is the tens of millions, we propose a simple algorithm to compress this graph without having read in the entire graph into the main memory. Our algorithm uses the quadtree data structure that is implicitly constructed to produce the compressed graph output. As a result of this implicit construction, our algorithm allows for node and edge additions/deletions that directly modifies the output compressed graph. We further develop algorithms to solve edge queries (is there any between two nodes?) and node queries (for a given node, list all its neighbors) that directly operates on the compressed graph. We have performed extensive empirical evaluations of our algorithms using publicly available, large social networks such as LiveJournal, Pokec, Twitter, and others. Our empirical evaluation is based on several parameters including time to compress, memory required by the compression algorithm, size of compressed graph, and time and memory size required to execute queries. We have also presented extensions to the compression algorithm that we have developed.

关键词： Social network services Image coding Matrix converters Arrays Computer science compression algorithms

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Interference detection using time-frequency binary hypothesis testing

Interference detection using time-frequency binary hypothesi...

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MILCOM, Military Communications Conference

作者： Andrew C. Marcum Joon Young Kim David J. Love James V. Krogmeier Raytheon Company Space and Airborne Systems Fort Wayne IN School of Electrical and Computer Engineering Purdue University West Lafayette IN

ISBN: (纸本)9781509000746

The growth in demand for wireless broadband is increasing the instrumental value of characterizing interference in spectral bands of interest. In particular, detection and classification of interference is an important function for mobile ad hoc network (MANET) nodes to optimize performance. In this paper, we propose interference detection and classification techniques for a network that consists of N distributed nodes and a classification center connected to each node by a robust link. Due to the limited capacity of the network connecting these nodes, each node compresses the observed signal into a binary vector that spans time and frequency and provides the bits to a classification center. In turn, the classification center stitches the compressed signals from all nodes into a single structure with characteristics that are exploited to detect and classify. The Kolmorgorov-Smirnov test is proposed for node compression. Furthermore, bounds on theoretical classification performance from finite blocklength coding theory are defined. Finally, we propose a minimum distance method to perform classification.

关键词： Interference Time-frequency analysis Mobile ad hoc networks Signal processing Detectors compression algorithms

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Huffman coding analysis of XOR filtered images

Huffman coding analysis of XOR filtered images

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IEEE International Symposium on Signal Processing and Information Technology (ISSPIT)

作者： Takiyah K. Cooper Ahmed H. Desoky CECS Department University of Louisville Louisville KY USA

The field of lossless image compression studies the various ways to represent image data in the most compact and efficient manner possible that also allows the image to be reproduced without any loss. There are many ways that this is accomplished and the most efficient strategy is to leverage the fundamental concepts of entropy reduction through decorrelation. The application of decorrelation methodologies prior to entropy coding is a modeling-coding strategy that produces significant results. This study focuses on the usage of the exclusive-or logic operator as a decorrelation filter. The exclusive-or logic operator is simply and reversibly applied to continuous-tone images for the purpose of extracting differences between neighboring pixels. The results of the exclusive-or operator based decorrelation filter are then processed through entropy encoding using Huffman coding. Experiments indicate that the exclusive-or operator based decorrelation filter has a significant impact on reducing entropy and therefore compression results.

关键词： Image coding Decorrelation compression algorithms Huffman coding Entropy Algorithm design and analysis Complexity theory

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Depth Stream compression for Enhanced Real Time Fall Detection by Multiple Sensors 4

Depth Stream Compression for Enhanced Real Time Fall Detecti...

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4th IEEE International Conference on Consumer Electronics Berlin (ICCE-Berlin)

作者： Cippitelli, Enea Gasparrini, Samuele Gambi, Ennio Spinsante, Susanna Univ Politecn Marche Dept Informat Engn I-60131 Ancona Italy

ISBN: (纸本)9781479961658

A fall detection system using depth data acquired from a single Kinect sensor could be expanded by addition of more devices. The idea consists in equipping each sensor with an embedded board, in order to stream the collected depth data over a network, towards a central system, able to retrieve the data and process them. A preliminary evaluation of a low-complexity compression algorithm for depth streams is performed, and some encouraging results are presented.

关键词： assisted living data compression image coding medical image processing sensor fusion Kinect sensor depth data embedded board enhanced real time fall detection low-complexity depth stream compression multiple sensors Bandwidth compression algorithms PSNR Sensor systems Streaming media Transform coding

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Data warehousing of vehicle trajectory

Data warehousing of vehicle trajectory

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IEEE International Conference on Software Engineering and Service Sciences (ICSESS)

作者： Baicheng Tang Guicheng Shen Cailin Zhang School of information Beijing Wuzi University Beijing Beijing Province China

ISBN: (纸本)9781479983544

With the rising number of vehicles equipped with GPS system, a lot of vehicle trajectories are produced every day. At present researchers begin to study the vehicles' trajectory data. But the current trajectory compression technology cannot be very simple and will lose much information. Therefore, this paper puts forward a data warehousing design of vehicle trajectory. It can store compressed vehicle trajectory, simplify the data volume, and save the feature points. Thus, it provides a sound base for finding useful information from vehicle trajectory.

关键词： Vehicles Trajectory Data warehouses Roads Global Positioning System compression algorithms Data mining

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A compression Algorithm for Real-Time Distributed Nonlinear MPC

A Compression Algorithm for Real-Time Distributed Nonlinear ...

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European Control Conference

作者： Rien Quirynen Mario Zanon Attila Kozma Moritz Diehl Department ESAT-STADIUS/OPTEC KU Leuven University

ISBN: (纸本)9781467371605

Model Predictive Control (MPC) requires the online solution of an Optimal Control Problem (OCP) at each sampling time. Efficient online algorithms such as the Real-Time Iteration (RTI) scheme have been developed for real-time MPC implementations even for fast nonlinear dynamic systems. The RTI framework is based on direct Multiple Shooting (MS) for centralized systems. Distributed Multiple Shooting (DMS) is an MS-based OCP discretization strategy for distributed systems. Many fast dynamic systems can be described as connected subsystems and in order to exploit this structure, a DMS based RTI scheme has been developed and implemented in ACADO code generation. A novel technique called compression is proposed to reduce the dimensions of the convex subproblem, while exploiting the coupling structure. The performance of the presented scheme is illustrated on a nontrivial example from the literature, where a speedup of factor 11 in simulation time and factor 6 in the total computation time can be shown over the classical RTI scheme.

关键词： RELATIVE THERMAL INDEX Maximum Allowable Concentration computational time compression algorithms multiple blasting Speeding Real time Open circuit potential

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