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Binary RDF representation for publication and exchange (HDT)

JOURNAL OF WEB SEMANTICS 2013年 19卷 22-41页

作者： Fernandez, Javier D. Martinez-Prieto, Miguel A. Gutierrez, Claudio Polleres, Axel Arias, Mario Univ Valladolid Dept Comp Sci ETS Ingn Informat DataWeb Res E-47011 Valladolid Spain Univ Chile Dept Comp Sci Santiago 8370459 Chile Natl Univ Ireland Digital Enterprise Res Inst Galway Ireland Siemens AG Osterreich A-1210 Vienna Austria

The current Web of data is producing increasingly large RDF datasets. Massive publication efforts of RDF data driven by initiatives like the Linked Open data movement, and the need to exchange large datasets has unveiled the drawbacks of traditional RDF representations, inspired and designed by a document-centric and human-readable Web. Among the main problems are high levels of verbosity/redundancy and weak machine-processable capabilities in the description of these datasets. This scenario calls for efficient formats for publication and exchange. This article presents a binary RDF representation addressing these issues. Based on a set of metrics that characterizes the skewed structure of real-world RDF data, we develop a proposal of an RDF representation that modularly partitions and efficiently represents three components of RDF datasets: Header information, a Dictionary, and the actual Triples structure (thus called HDT). Our experimental evaluation shows that datasets in HDT format can be compacted by more than fifteen times as compared to current naive representations, improving both parsing and processing while keeping a consistent publication scheme. Specific compression techniques over HDT further improve these compression rates and prove to outperform existing compression solutions for efficient RDF exchange. (c) 2013 Elsevier B.V. All rights reserved.

关键词： RDF Binary formats data compaction and compression RDF metrics

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The VPC trace-compression algorithms

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IEEE TRANSACTIONS ON COMPUTERS 2005年第11期54卷 1329-1344页

作者： Burtscher, M Ganusov, I Jackson, SJ Ke, J Ratanaworabhan, P Sam, NB Cornell Univ Sch Elect & Comp Engn Ithaca NY 14853 USA

Execution traces, such as are used to study and analyze program behavior, are often so large that they need to be stored in compressed form. This paper describes the design and implementation of four value prediction-based compression (VPC) algorithms for traces that record the PC as well as other information about executed instructions. VPC1 directly compresses traces using value predictors, VPC2 adds a second compression stage, and VPC3 utilizes value predictors to convert traces into streams that can be compressed better and more quickly than the original traces. VPC4 introduces further algorithmic enhancements and is automatically synthesized. Of the 55 SPECcpu2000 traces we evaluate, VPC4 compresses 36 better, decompresses 26 faster, and compresses 53 faster than BZIP2, MACHE, PDATS II, SBC, and SEQUITUR. It delivers the highest geometric-mean compression rate, decompression speed, and compression speed because of the predictors' simplicity and their ability to exploit local value locality. Most other compression algorithms can only exploit global value locality.

关键词： data compaction and compression performance analysis and design aids

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Pattern Matching Techniques for Replacing Missing Sections of Audio Streamed across Wireless Networks

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ACM TRANSACTIONS ON INTELLIGENT SYSTEMS AND TECHNOLOGY 2015年第2期6卷 1–38页

作者： Doherty, Jonathan Curran, Kevin Mckevitt, Paul Univ Ulster Sch Comp & Intelligent Syst Derry North Ireland

Streaming media on the Internet can be unreliable. Services such as audio-on-demand drastically increase the loads on networks;therefore, new, robust, and highly efficient coding algorithms are necessary. One method overlooked to date, which can work alongside existing audio compression schemes, is that which takes into account the semantics and natural repetition of music. Similarity detection within polyphonic audio has presented problematic challenges within the field of music information retrieval. One approach to deal with bursty errors is to use self-similarity to replace missing segments. Many existing systems exist based on packet loss and replacement on a network level, but none attempt repairs of large dropouts of 5 seconds or more. Music exhibits standard structures that can be used as a forward error correction (FEC) mechanism. FEC is an area that addresses the issue of packet loss with the onus of repair placed as much as possible on the listener's device. We have developed a server-client-based framework (SoFI) for automatic detection and replacement of large packet losses on wireless networks when receiving time-dependent streamed audio. Whenever dropouts occur, SoFI swaps audio presented to the listener between a live stream and previous sections of the audio stored locally. Objective and subjective evaluations of SoFI where subjects were presented with other simulated approaches to audio repair together with simulations of replacements including varying lengths of time in the repair give positive results.

关键词： Streaming Audio Streaming media forward error correction audio repair data compaction and compression

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Trading Off Accuracy, Timeliness, and Uplink Usage in Online GPS Tracking

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IEEE TRANSACTIONS ON MOBILE COMPUTING 2016年第8期15卷 2124-2136页

作者： Musa, A. B. M. Biagioni, James Eriksson, Jakob Univ Illinois Dept Comp Sci Chicago IL 60607 USA

In an online GPS tracking system, a fundamental trade-off exists between timeliness, the average time interval between a recorded change in location and a change in the reported location;accuracy, the average error between the actual location and the reported location;and uplink usage, the average amount of data used per second of tracking. While tracking efficiency has been addressed in the literature, our thrifty tracking system presents the first unified view of timeliness, accuracy, and uplink usage, allowing the user to specify desired targets for any two of these objectives, while optimizing the third. We also provide a closed-form characterization of this three-way trade-off, and demonstrate that our system converges to the predicted performance.

关键词： Spatial databases and GIS mobile communication systems mobile computing client/server data compaction and compression data communications data communications aspects system applications and experience

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Edgebreaker: a simple implementation for surfaces with handles

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COMPUTERS & GRAPHICS-UK 2003年第4期27卷 553-567页

作者： Lopes, H Rossignac, J Safonova, A Szymczak, A Tavares, G Pontificia Univ Catolica Rio de Janeiro Dept Matemat BR-22453900 Rio De Janeiro Brazil Georgia Inst Technol Coll Comp Atlanta GA 30332 USA Georgia Inst Technol GVU Ctr Atlanta GA 30332 USA Carnegie Mellon Univ Dept Comp Sci Pittsburgh PA 15213 USA

The Edgebreaker is an efficient scheme for compressing triangulated surfaces. A surprisingly simple implementation of Edgebreaker has been proposed for surfaces homeomorphic to a sphere. It uses the corner-table data structure, which represents the connectivity of a triangulated surface by two tables of integers, and encodes them with less than 2 bits per triangle. We extend this simple formulation to deal with triangulated surfaces with handles and present the detailed pseudocode for the encoding and decoding algorithms (which take one page each). We justify the validity of the proposed approach using the mathematical formulation of the handlebody theory for surfaces, which explains the topological changes that occur when two boundary edges of a portion of a surface are identified. (C) 2003 Elsevier Ltd. All rights reserved.

关键词： data compaction and compression data storage representations boundary representations graphs and algorithms handlebody theory

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ACM TRANSACTIONS ON MULTIMEDIA COMPUTING COMMUNICATIONS AND APPLICATIONS 2013年第3期9卷 1–20页

作者： Doherty, Jonathan Curran, Kevin Mckevitt, Paul Univ Ulster Sch Comp & Intelligent Syst Derry North Ireland

Enjoyment of audio has now become about flexibility and personal freedom. Digital audio content can be acquired from many sources and wireless networking allows digital media devices and associated peripherals to be unencumbered by wires. However, despite recent improvements in capacity and quality of service, wireless networks are inherently unreliable communications channels for the streaming of audio, being susceptible to the effects of range, interference, and occlusion. This time-varying reliability of wireless audio transfer introduces data corruption and loss, with unpleasant audible effects that can be profound and prolonged in duration. Traditional communications techniques for error mitigation perform poorly and in a bandwidth inefficient manner in the presence of such large-scale defects in a digital audio stream. A novel solution that can complement existing techniques takes account of the semantics and natural repetition of music. Through the use of self-similarity metadata, missing or damaged audio segments can be seamlessly replaced with similar undamaged segments that have already been successfully received. We propose a technology to generate relevant self-similarity metadata for arbitrary audio material and to utilize this metadata within a wireless audio receiver to provide sophisticated and real-time correction of large-scale errors. The primary objectives are to match the current section of a song being received with previous sections while identifying incomplete sections and determining replacements based on previously received portions of the song. This article outlines our approach to Forward Error Correction (FEC) technology that is used to "repair" a bursty dropout when listening to time-dependent media on a wireless network. Using self-similarity analysis on a music file, we can "automatically" repair the dropout with a similar portion of the music already received thereby minimizing a listener's discomfort.

关键词： Performance Streaming audio streaming media forward error correction audio repair data compaction and compression

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Advanced techniques for high-quality multi-resolution volume rendering

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COMPUTERS & GRAPHICS-UK 2004年第1期28卷 51-58页

作者： Guthe, S Strasser, W Univ Tubingen GRIS WSI D-72076 Tubingen Germany

We present several improvements for compression-based multi-resolution rendering of very large volume data sets at interactive to real-time frame rates on standard PC hardware. The algorithm accepts scalar or multi-variant data sampled on a regular grid as input. The input data are converted into a compressed hierarchical wavelet representation in a pre-processing step. During rendering, the wavelet representation is decompressed on-the-fly and rendered using hardware texture mapping. The level-of-detail used for rendering is adapted to the estimated screen-space error. To.-increase the rendering performance additional visibility tests, such as empty space skipping and occlusion culling, are applied. Furthermore, we discuss how to render the remaining multi-resolution blocks efficiently using modern graphics hardware. Using a prototype implementation of this algorithm we are able to perform a high-quality interactive rendering of large data sets on a single off-the-shelf PC. (C) 2003 Elsevier Ltd. All rights reserved.

关键词： viewing algorithms data compaction and compression

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A Communication Perspective on Automatic Text Categorization

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IEEE TRANSACTIONS ON KNOWLEDGE AND data ENGINEERING 2009年第7期21卷 1027-1041页

作者： Capdevila, Marta Marquez Florez, Oscar W. Univ Vigo Signal & Commun Proc Dept Telecommun Engn Sch E-36310 Vigo Spain

The basic concern of a Communication System is to transfer information from its source to a destination some distance away. Textual documents also deal with the transmission of information. Particularly, from a text categorization system point of view, the information encoded by a document is the topic or category it belongs to. Following this initial intuition, a theoretical framework is developed where Automatic Text Categorization (ATC) is studied under a Communication System perspective. Under this approach, the problematic indexing feature space dimensionality reduction has been tackled by a two-level supervised scheme, implemented by a noisy terms filtering and a subsequent redundant terms compression. Gaussian probabilistic categorizers have been revisited and adapted to the concomitance of sparsity in ATC. Experimental results pertaining to 20 Newsgroups and Reuters-21578 collections validate the theoretical approaches. The noise filter and redundancy compressor allows an aggressive term vocabulary reduction ( reduction factor greater than 0.99) with a minimum loss ( lower than 3 percent) and, in some cases, gain ( greater than 4 percent) of final classification accuracy. The adapted Gaussian Naive Bayes classifier reaches classification results similar to those obtained by state-of-the-art Multinomial Naive Bayes (MNB) and Support Vector Machines (SVMs).

关键词： data communications text processing data compaction and compression clustering classifier design and evaluation feature evaluation and selection

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Multi-Prediction compression: An Efficient and Scalable Memory compression Framework for GP-GPU

IEEE COMPUTER ARCHITECTURE LETTERS

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IEEE COMPUTER ARCHITECTURE LETTERS 2022年第2期21卷 37-40页

作者： Jin, Hoyong Jeong, Donghun Park, Taewon Ko, Jong Hwan Kim, Jungrae Sungkyunkwan Univ Dept Elect & Comp Engn Suwon 16419 South Korea Sungkyunkwan Univ Dept Semicond & Display Engn Suwon 16419 South Korea

data-intensive applications and throughput-oriented processors demand more memory bandwidth. Memory compression can provide more data beyond physical limits, yet new data types and smaller block sizes are challenging. This paper presents a novel and lightweight memory compression framework, Multi-Prediction compression (MPC), to increase the effective memory bandwidth. Based on multiple prediction models and data-driven algorithm tuning, MPC can provide 31.7% better compression than state-of-the-art (SOTA) algorithms for 32B blocks. Moreover, MPC is hardware-friendly and scalable to support a growing number of data patterns.

关键词： Predictive models data models Correlation Prediction algorithms Transformers Hardware Bandwidth Graphics processors memory hierarchy data compaction and compression

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Time Series Management Systems: A Survey

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IEEE TRANSACTIONS ON KNOWLEDGE AND data ENGINEERING 2017年第11期29卷 2581-2600页

作者： Jensen, Soren Kejser Pedersen, Torben Bach Thomsen, Christian Aalborg Univ Dept Comp Sci DK-9100 Aalborg Denmark

The collection of time series data increases as more monitoring and automation are being deployed. These deployments range in scale from an Internet of things (IoT) device located in a household to enormous distributed Cyber-Physical Systems (CPSs) producing large volumes of data at high velocity. To store and analyze these vast amounts of data, specialized Time Series Management Systems (TSMSs) have been developed to overcome the limitations of general purpose database Management Systems (DBMSs) for times series management. In this paper, we present a thorough analysis and classification of TSMSs developed through academic or industrial research and documented through publications. Our classification is organized into categories based on the architectures observed during our analysis. In addition, we provide an overview of each system with a focus on the motivational use case that drove the development of the system, the functionality for storage and querying of time series a system implements, the components the system is composed of, and the capabilities of each system with regard to Stream Processing and Approximate Query Processing (AQP). Last, we provide a summary of research directions proposed by other researchers in the field and present our vision for a next generation TSMS.

关键词： Approximation cyber-physical systems data abstraction data compaction and compression data storage representations data structures database architectures distributed databases distributed systems internet of things scientific databases sensor data sensor networks stream processing time series analysis

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