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data-Aware Adaptive compression for Stream Processing

IEEE TRANSACTIONS ON KNOWLEDGE AND data ENGINEERING 2024年第9期36卷 4531-4549页

作者： Zhang, Yu Zhang, Feng Li, Hourun Zhang, Shuhao Guo, Xiaoguang Chen, Yuxing Pan, Anqun Du, Xiaoyong Renmin Univ China Sch Informat Key Lab Data Engn & Knowledge Engn MOE Beijing 100872 Peoples R China Nanyang Technol Univ NTU Sch Comp Sci & Engn SCSE Singapore 639798 Singapore Tencent Inc Database R&D Dept Shenzhen Peoples R China

Stream processing has been in widespread use, and one of the most common application scenarios is SQL query on streams. By 2021, the global deployment of IoT endpoints reached 12.3 billion, indicating a surge in data generation. However, the escalating demands for high throughput and low latency in stream processing systems have posed significant challenges due to the increasing data volume and evolving user requirements. We present a compression-based stream processing engine, called CompressStreamDB, which enables adaptive fine-grained stream processing directly on compressed streams, to significantly enhance the performance of existing stream processing solutions. CompressStreamDB utilizes nine diverse compression methods tailored for different stream data types and integrates a cost model to automatically select the most efficient compression schemes. CompressStreamDB provides high throughput with low latency in stream SQL processing by identifying and eliminating redundant data among streams. Our evaluation demonstrates that CompressStreamDB improves average performance by 3.84x and reduces average delay by 68.0% compared to the state-of-the-art stream processing solution for uncompressed streams, along with 68.7% space savings. Besides, our edge trials show an average throughput/price ratio of 9.95x and a throughput/power ratio of 7.32x compared to the cloud design.

关键词： Encoding compression algorithms Real-time systems Low latency communication data processing Costs Delays data compaction and compression stream processing edge computing

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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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Interactive level-of-detail selection using image-based quality metric for large volume visualization

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IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS 2007年第1期13卷 122-134页

作者： Wang, Chaoli Garcia, Antonio Shen, Han-Wei Ohio State Univ Dept Comp Sci & Engn Columbus OH 43210 USA Intel Corp Bellevue WA 98007 USA

For large volume visualization, an image-based quality metric is difficult to incorporate for level-of-detail selection and rendering without sacrificing the interactivity. This is because it is usually time-consuming to update view-dependent information as well as to adjust to transfer function changes. In this paper, we introduce an image-based level-of-detail selection algorithm for interactive visualization of large volumetric data. The design of our quality metric is based on an efficient way to evaluate the contribution of multiresolution data blocks to the final image. To ensure real-time update of the quality metric and interactive level-of-detail decisions, we propose a summary table scheme in response to runtime transfer function changes and a GPU-based solution for visibility estimation. Experimental results on large scientific and medical data sets demonstrate the effectiveness and efficiency of our algorithm.

关键词： data compaction and compression perceptual reasoning viewing algorithms interaction techniques hierarchical image representation volume visualization

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Improved word-aligned binary compression for text indexing

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IEEE TRANSACTIONS ON KNOWLEDGE AND data ENGINEERING 2006年第6期18卷 857-861页

作者： Anh, VN Moffat, A Univ Melbourne Dept Comp Sci & Software Engn Melbourne Vic 3010 Australia

We present an improved compression mechanism for handling the compressed inverted indexes used in text retrieval systems, extending the word-aligned binary coding carry method. Experiments using two typical document collections show that the new method obtains superior compression to previous static codes, without penalty in terms of execution speed.

关键词： data compaction and compression textual databases indexing methods file organization compression inverted index binary code text retrieval system text searching Web searching

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A Selective Encryption Scheme with Multiple security Levels for the H. 264/AVC Video Coding 16

A Selective Encryption Scheme with Multiple security Levels ...

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IEEE International Conference on Computer and Information Technology (CIT)

作者： Sbiaa, F. Kotel, S. Zeghid, M. Tourki, R. Machhout, M. Baganne, A. Univ South Brittany Lab Informat Sci & Technol Commun & Knowledge Lab STICC Lorient France Univ Monastir Fac Sci Elect & Microelect Lab Monastir 5019 Tunisia

ISBN: (纸本)9781509043149

The H. 264 Advanced Video Coding (H. 264/AVC) standard is considered to be the most commonly used format for video compression. Although it supports a very broad applications range covering all forms of digital compressed video, the confidentiality of the encoded content needs enhancements. The present work proposes a new selective encryption scheme with multiple security levels. In fact, depending on the encrypted coefficients nature, five different cryptographic scenarios are proposed. They provide an effective confidentiality and deal with the real-time processing requirements. The Hardware/Software co-simulation and the experimental results proved the efficiency of the proposed crypto-system that will be suitable for real-time video applications and resource-limited systems.

关键词： Video coding Coding and Information Theory data encryption data compaction and compression

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Applications of forman's discrete Morse theory to topology visualization and mesh compression

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IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS 2004年第5期10卷 499-508页

作者： Lewiner, T Lopes, H Tavares, G Pontificia Univ Catolica Rio de Janeiro Dept Matemat Lab MatMidia BR-22453900 Rio De Janeiro Brazil

Morse theory is a powerful tool for investigating the topology of smooth manifolds. It has been widely used by the computational topology, computer graphics, and geometric modeling communities to devise topology-based algorithms and data structures. Forman introduced a discrete version of this theory which is purely combinatorial. This work aims to build, visualize, and apply the basic elements of Forman's discrete Morse theory. It intends to use some of those concepts to visually study the topology of an object. As a basis, an algorithmic construction of optimal Forman's discrete gradient vector fields is provided. This construction is then used to topologically analyze mesh compression schemes, such as Edgebreaker and Grow&Fold. In particular, this paper proves that the complexity class of the strategy optimization of Grow&Fold is MAX-SNP hard.

关键词： discrete mathematics hypergraphs data compaction and compression computer fraphics computer-aided design

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compression of Multiple DNA Sequences Using Intra-Sequence and Inter-Sequence Similarities

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IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS 2015年第6期12卷 1322-1332页

作者： Cheng, Kin-On Wu, Paula Law, Ngai-Fong Siu, Wan-Chi Hong Kong Polytech Univ Dept Elect & Informat Engn Ctr Signal Proc Hong Kong Hong Kong Peoples R China

Traditionally, intra-sequence similarity is exploited for compressing a single DNA sequence. Recently, remarkable compression performance of individual DNA sequence from the same population is achieved by encoding its difference with a nearly identical reference sequence. Nevertheless, there is lack of general algorithms that also allow less similar reference sequences. In this work, we extend the intra-sequence to the inter-sequence similarity in that approximate matches of subsequences are found between the DNA sequence and a set of reference sequences. Hence, a set of nearly identical DNA sequences from the same population or a set of partially similar DNA sequences like chromosome sequences and DNA sequences of related species can be compressed together. For practical compressors, the compressed size is usually influenced by the compression order of sequences. Fast search algorithms for the optimal compression order are thus developed for multiple sequences compression. Experimental results on artificial and real datasets demonstrate that our proposed multiple sequences compression methods with fast compression order search are able to achieve good compression performance under different levels of similarity in the multiple DNA sequences.

关键词： Biology and genetics data compaction and compression data dependencies information theory

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compression of Solar Spectroscopic Observations: a Case Study of MgII k Spectral Line Profiles Observed by NASA's IRIS Satellite 18

Compression of Solar Spectroscopic Observations: a Case Stud...

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18th International Conference on Content-Based Multimedia Indexing (IEEE CBMI)

作者： Sadykov, Viacheslav M. Kitiashvili, Irina N. Dalda, Alberto Sainz Oria, Vincent Kosovichev, Alexander G. Illarionov, Egor Georgia State Univ Dept Phys & Astron Atlanta GA 30303 USA NASA Supercomp Div Ames Res Ctr Moffett Field CA USA Lockheed Martin Solar & Astrophys Lab Palo Alto CA USA New Jersey Inst Technol Dept Comp Sci Newark NJ USA New Jersey Inst Technol Dept Phys Newark NJ 07102 USA Moscow MV Lomonosov State Univ Dept Mech & Math Moscow Russia

ISBN: (纸本)9781665442206

In this study we extract the deep features and investigate the compression of the MgII k spectral line profiles observed in quiet Sun regions by NASA's IRIS satellite. The data set of line profiles used for the analysis was obtained on April 20th, 2020, at the center of the solar disc, and contains almost 300,000 individual MgII k line profiles after data cleaning. The data are separated into train and test subsets. The train subset was used to train the autoencoder of the varying embedding layer size. The early stopping criterion was implemented on the test subset to prevent the model from overfitting. Our results indicate that it is possible to compress the spectral line profiles more than 27 times (which corresponds to the reduction of the data dimensionality from 110 to 4) while having a 4DN (data Number) average reconstruction error, which is comparable to the variations in the line continuum. The mean squared error and the reconstruction error of even statistical moments sharply decrease when the dimensionality of the embedding layer increases from 1 to 4 and almost stop decreasing for higher numbers. The observed occasional improvements in training for values higher than 4 indicate that a better compact embedding may potentially be obtained if other training strategies and longer training times are used. The features learned for the critical four-dimensional case can be interpreted. In particular, three of these four features mainly control the line width, line asymmetry, and line dip formation respectively. The presented results are the first attempt to obtain a compact embedding for spectroscopic line profiles and confirm the value of this approach, in particular for feature extraction, data compression, and denoising.

关键词： Machine learning Neural nets data compaction and compression Feature extraction or construction

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A GPU Register File using Static data compression 20

A GPU Register File using Static Data Compression

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49th International Conference on Parallel Processing (ICPP)

作者： Angerd, Alexandra Sintorn, Erik Stenstrom, Per Chalmers Univ Technol Dept Comp Sci & Engn Gothenburg Sweden

ISBN: (纸本)9781450388160

GPUs rely on large register files to unlock thread-level parallelism for high throughput. Unfortunately, large register files are power hungry, making it important to seek for new approaches to improve their utilization. This paper introduces a new register file organization for efficient register-packing of narrow integer and floating-point operands designed to leverage on advances in static analysis. We show that the hardware/software co-designed register file organization yields a performance improvement of up to 79%, and 18.6%, on average, at a modest output-quality degradation.

关键词： Graphics processors Micro-architecture implementation considerations data compaction and compression Approximation

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Radio Channel Transmission of Signals with Variance Shift Keying 28

Radio Channel Transmission of Signals with Variance Shift Ke...

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28th Telecommunications Forum (TELFOR)

作者： Sokolov, Rostislav, I Abdullin, Renat R. Ural Fed Univ Engn Sch Informat Technol Telecommun & Control Sy Mira St 19 Ekaterinburg 620002 Russia

ISBN: (纸本)9780738142432

The present work is aimed to experimentally confirm the prospects of wireless communication using the previously developed noise-like ultra wideband signal. This signal is a white Gaussian noise, whose variance change in accordance to modulating informational sequence. The main purpose is to check how the spectrum of developed signal changes going through the narrowband antennas and frequency selective media, and how this affects the possibility of restoration at the receiver site. Biquad antennas of 1800 MHz GSM range are used in the full-scale experiment. The experiment proves that extraction of information from mixture of the developed signal with external interference of natural origin is really achievable.

关键词： Correlation and regression analysis data compaction and compression Information hiding Random number generation Signal processing Wireless communication

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