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International Conference on Communication Technology (ICCT)

作者： Chenxu Wang Youyun Xu School of Communication and Information Engineering Nanjing University of Posts and Telecommunications Nanjing China National Engineering Research Center of Communications and Networking Nanjing China

ISBN: (数字)9798350363760

ISBN: (纸本)9798350363777

Reconfigurable intelligent surface is a promising technology for enhancing wireless communication in various scenarios. Despite its promise, utilizing reconfigurable intelligent surface for communication services poses non-convex optimization challenges. In this paper, we propose a hybrid beamforming algorithm for reconfigurable intelligent surface aided mmWave vehicle-to-everything communication systems to maximize the system’s sum rate. The proposed algorithm is an iterative process developed jointly using coati optimization algorithm, group selection and codebook compression for reconfigurable intelligent surface aided beamforming. The algorithm first selects the reconfigurable intelligent surface phase shift matrix, then groups the vehicular user equipments and utilizes codebook compression algorithm to compute the beamforming matrix. The algorithm runs until it finds the maximum sum rate. Simulation results have verified the effectiveness of the proposed algorithm as compared to different benchmark schemes.

关键词： Wireless communication Correlation Array signal processing Simulation Reconfigurable intelligent surfaces Iterative algorithms Millimeter wave communication Optimization compression algorithms Vehicle-to-everything

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A Method for Compressed Storage and Retrieval of Triplet Data Based on Cuckoo Hashing

A Method for Compressed Storage and Retrieval of Triplet Dat...

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International Conference on Wavelet Active Media Technology and Information Processing (ICWAMTIP)

作者： Liu Pengcheng Qinzhi Zhang Shibin Chang Yan Yan Lili School of Cybersecurity (Xin Gu Industrial College) Chengdu University of Information Technology Chengdu China Advanced Cryptography and System Security Key Laboratory of Sichuan Province Chengdu China SUGON Industrial Control and Security Center Chengdu China

ISBN: (数字)9798331519254

ISBN: (纸本)9798331519261

This paper proposes a method for compressing and retrieving triple data based on optimized cuckoo hash. Firstly, the optimized cuckoo hash algorithm is utilized to quickly establish node indexes. Then, the relationship information of triples is stored in the form of a sparse matrix according to the relationship type. Finally, the double compression algorithm k 2 -Rel is employed to compress the relationship attribute matrix of stored triple information, aiming to reduce storage space and lower storage costs. Experimental results demonstrate that the optimized cuckoo hash algorithm significantly reduces the time for building node indexes. Furthermore, utilizing the k2-Rel compression algorithm for compressing the relationship information between nodes substantially decreases storage space, ultimately achieving efficient storage and retrieval of triple data.

关键词： Costs Triples (Data structure) Buildings Information processing Media Motion pictures Sparse matrices Indexes compression algorithms

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GeoSecure-B:A Method for Secure Bearing Calculation

GeoSecure-B:A Method for Secure Bearing Calculation

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IEEE Conference on Multimedia Information Processing and Retrieval (MIPR)

作者： Vikram Patil Sharmilee Rajkumar Rajan Pradeep K. Atrey Albany Lab for Privacy and Security University at Albany SUNY Albany NY USA GoDaddy LLC Hoboken NJ USA

ISBN: (数字)9798350351422

ISBN: (纸本)9798350351439

Location-Based Services (LBS) applications are everywhere these days. Detecting the heading or bearing is crucial for many of these applications, as it indicates the direction the user is moving. This information is typically derived from the GPS trajectory of the user. However, because GPS data can reveal sensitive information, such as a user's location, there are privacy concerns associated with its use. Therefore, there's a need to devise a solution that safeguards GPS data from potential adversaries. Although multiple techniques for calculating bearing are documented in the literature, this paper presents a secure method, called GeoSecure- B,for calculating bearing based on GPS coordinates while preserving user location privacy. Our methodology is assessed using Microsoft's GeoLife dataset, demonstrating that our results closely align with bearings calculated from methodologies utilizing real GPS coordinates.

关键词： Privacy Data privacy Geology Information processing Cleaning Trajectory compression algorithms Global Positioning System

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Data Recovery Method for Truncated Gzip Compressed Files

Data Recovery Method for Truncated Gzip Compressed Files

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International Conference on Fuzzy Systems and Knowledge Discovery (FSKD)

作者： Wenjie Luo Jian Wu Chengxiang Chen Fenghua Liu State Grid Shanghai Urban Electric Power Supply Company State Grid Shanghai Municipal Electric Power Company Shanghai P.R. China State Grid Shanghai Shibei Electric Power Supply Company State Grid Shanghai Municipal Electric Power Company Shanghai P.R. China State Grid Quanzhou Electric Power Supply Company State Grid Fujian Electric Power Co. Ltd Quanzhou P. R. China State Grid Shanghai Pudong Electric Power Supply Company State Grid Shanghai Municipal Electric Power Company Shanghai P.R. China

ISBN: (数字)9798350356328

ISBN: (纸本)9798350356335

Data recovery for truncated gzip compressed files is a critical task in various industries and open-source communities where gzip compression is widely utilized for its efficiency in reducing file sizes while maintaining data integrity. This paper presents a method of data recovery for truncated gzip compressed files, focusing on the principles, implementation, efficiency, and implications of such a method. The first part of the paper provides an in-depth introduction to the gzip file format and the binary construction of gzip files is outlined. The second part of the paper introduces a principle-based approach to data recovery for truncated gzip compressed files, which involves iteratively removing extraneous bits from the beginning of the truncated file until a complete DEFLATE block is obtained, enabling successful decoding of the file. Implementation details of this approach, including the iterative decoding process and its impact on data recovery efficiency, are discussed in detail. The third part of the paper evaluates the efficiency of the data recovery method, focusing on the impact of DEFLATE block size and the iterative decoding process. Smaller DEFLATE blocks are found to facilitate quick data recovery, while the iterative decoding process incrementally narrows down the search space for the first complete DEFLATE block. Tradeoffs and considerations associated with the iterative decoding process are also discussed, highlighting the importance of ongoing research and development efforts to further improve data recovery efficiency. By leveraging principles of the gzip file format and DEFLATE compression, it is possible to develop effective data recovery techniques that can recover significant portions of the original uncompressed data from truncated gzip compressed files.

关键词： Industries Heuristic algorithms Data integrity Focusing Knowledge discovery Computational efficiency Iterative decoding Research and development compression algorithms Fuzzy systems

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A Cooperative Sensor-Based Navigational Concept for Heterogeneous AUV Swarms

A Cooperative Sensor-Based Navigational Concept for Heteroge...

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OCEANS Conference

作者： Cimiega, Thomas Badri-Hoeher, Sabah Univ Appl Sci Kiel Fac Comp Sci & Elect Engn Kiel Germany

ISBN: (纸本)9780692935590

In this work a navigational concept for a heterogeneous swarm of AUVs is treated. Inspired by search and rescue manoeuvres of emergency forces, the swarm consists of two types of agents that detect and inspect possible objects of interest like contaminations of munition, crash sites or pipeline leaks. Each agent type differs by its degrees of freedom, environmental sensors, navigational devices and software defined role. The main part of this work is the obligatory and optimized information exchange between the agent types to localize and inspect objects of interest. To evaluate the concept, a simulation environment for autonomous agents using the proposed algorithms for target localization is realized. Since this work is a general representation of a powerful concept, we use two common feature extraction methods for information encoding. First, we use Ri-HOG because it is deterministic in parametrization and results. On the other hand, we use artificial neural networks since they provide excellent results for image-related tasks such as segmentation, reconstruction, and object classification. Both methods are evaluated for their ability to reference the same object in two images with short feature vectors. We then test the performance of the methods as well as the advantageous concept of heterogeneous swarm behavior in terms of mission time and power consumption using an underwater simulation that uses synthetic sonar image data.

关键词： multi-agent systems autonomous vehicles cooperative systems search methods object recognition neural networks acoustics compression algorithms

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Physical Layer Authentication Techniques based on Machine Learning with Data compression

Physical Layer Authentication Techniques based on Machine Le...

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IEEE Conference on Communications and Network Security (CNS)

作者： Senigagliesi, Linda Baldi, Marco Gambi, Ennio Univ Politecn Marche Dept Informat Engn I-60131 Ancona Italy

ISBN: (纸本)9781728147604

Wireless communications employing multi-carrier transmissions, like orthogonal frequency division multiplexing (OFDM) or single-carrier frequency division multiple access (SC-FDMA) may involve the use of a large number of subcarriers. In Internet of Things (IoT) contexts, however, the use of such technologies implies the fast management of large amounts of samples on devices with limited memory and computational resources. The adoption of physical layer authentication protocols in IoT may suffer from this fact, especially when they exploit machine learning algorithms yielding a significant computational burden. For instance, the complexity of Nearest Neighbor classifiers strictly depends on the training set dimension, which is directly proportional to the number of used subcarriers. In order to deal with this issue, we start from a naive approach based on random sampling of the input data to extract features, and then consider more advanced data dimension reduction algorithms, such as Principal Component Analysis (PCA) and t-distributed Stochastic Neighbor Embedding (t-SNE). We show that PCA is able to guarantee the best trade-off between authentication performance and complexity, while the application of t-SNE is effective when one wants to reduce data to a very small number of features.

关键词： authentication compression algorithms machine learning physical layer security wireless networks

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Hardware Implementation of the CCSDS 123.0-B-2 Near-Lossless compression Standard Following an HLS Design Methodology

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REMOTE SENSING 2021年第21期13卷 4388-4388页

作者： Barrios, Yubal Sanchez, Antonio Guerra, Raul Sarmiento, Roberto Univ Las Palmas de Gran Canaria ULPGC Inst Appl Microelect IUMA Las Palmas Gran Canaria 35017 Spain

The increment in the use of high-resolution imaging sensors on-board satellites motivates the use of on-board image compression, mainly due to restrictions in terms of both hardware (computational and storage resources) and downlink bandwidth with the ground. This work presents a compression solution based on the CCSDS 123.0-B-2 near-lossless compression standard for multi- and hyperspectral images, which deals with the high amount of data acquired by these next-generation sensors. The proposed approach has been developed following an HLS design methodology, accelerating design time and obtaining good system performance. The compressor is comprised by two main stages, a predictor and a hybrid encoder, designed in Band-Interleaved by Line (BIL) order and optimized to achieve a trade-off between throughput and logic resources utilization. This solution has been mapped on a Xilinx Kintex UltraScale XCKU040 FPGA and targeting AVIRIS images, reaching a throughput of 12.5 MSamples/s and consuming only the 7% of LUTs and around the 14% of dedicated memory blocks available in the device. To the best of our knowledge, this is the first fully-compliant hardware implementation of the CCSDS 123.0-B-2 near-lossless compression standard available in the state of the art.

关键词： hyperspectral imaging compression algorithms FPGA hardware implementations space missions on-board data processing CCSDS

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Reducing Data Dependencies in the Feedback Loop of the CCSDS 123.0-B-2 Predictor

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IEEE GEOSCIENCE AND REMOTE SENSING LETTERS 2022年 19卷 1页

作者： Sanchez, Antonio Blanes, Ian Barrios, Yubal Hernandez-Cabronero, Miguel Bartrina-Rapesta, Joan Serra-Sagrista, Joan Sarmiento, Roberto Univ Las Palmas de Gran Canaria ULPGC Inst Appl Microelect IUMA Las Palmas Gran Canaria 35017 Spain Univ Autonoma Barcelona Dept Informat & Commun Engn E-08193 Barcelona Spain

On-board multi- and hyperspectral instruments acquire large volumes of data that need to be processed with the limited computational and storage resources. In this context, the Consultative Committee for Space Data Systems (CCSDS) 123.0-B-2 standard emerges as an interesting option to compress multi- and hyperspectral images on-board satellites, supporting both lossless and near-lossless compression with low complexity and reduced power consumption. Nonetheless, the inclusion of a feedback loop in the CCSDS 123.0-B-2 predictor to support near-lossless compression introduces significant data dependencies that hinder real-time processing, particularly due to the presence of a quantization stage within this loop. This work provides an analysis of the aforementioned data dependencies and proposes two strategies aiming at maximizing throughput in hardware implementations and thus enabling real-time processing. In particular, through an elaborate mathematical derivation, the quantization stage is removed completely from the feedback loop. This reduces the critical path, which allows for shorter initiation intervals in a pipelined hardware implementation and higher throughput. This is achieved without any impact on the compression performance, which is identical to the one obtained by the original data flow of the predictor.

关键词： Standards Quantization (signal) Throughput Hardware Image coding Feedback loop Optimization compression algorithms Consultative Committee for Space Data Systems (CCSDS) 1230-B-2 hyperspectral imaging onboard data processing

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Image Compressed Sensing Using Auxiliary Information for Efficient Coding

Image Compressed Sensing Using Auxiliary Information for Eff...

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Data compression Conference (DCC)

作者： Bo Zhang Di Xiao Dongjing Shan Communication NCO Academy Army Engineering University China College of Computer Science Chongqing University China The School of Electronics Engineering and Computer Science Peking University China

Compressed sensing (CS) has attracted wide attention in signal process field, which states that a sparse signal or a compressive signal can be reconstructed by using a small number of CS samples efficiently. In recent years, CS-based image coding methods have been investigated extensively. However, the ratio-distortion (R-D) performance of this method is unsatisfactory in comparison with traditional compression algorithms, such as JPEG and JPEG2000.

关键词： Image coding Transform coding Compressed sensing Image reconstruction compression algorithms

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Constructing the CDAWG CFG using LCP-Intervals

Constructing the CDAWG CFG using LCP-Intervals

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Data compression Conference (DCC)

作者： Alan Cleary Jordan Dood National Center for Genome Resources Santa Fe NM USA Montana State University Bozeman MT USA

It is known that a context-free grammar (CFG) that produces a single string can be derived from the compact directed acyclic word graph (CDAWG) for the same string. In this work, we show that the CFG derived from a CDAWG is deeply connected to the maximal repeat content of the string it produces and thus has O(m) rules, where m is the number of maximal repeats in the string. We then provide a generic algorithm based on this insight for constructing the CFG from the LCP-intervals of a string in O(n) time, where n is the length of the string. This includes a novel data-structure to support stabbing queries on LCPintervals in O(1+k) time after O(n) preprocessing time, where k is the number of intervals stabbed. These results connect the CFG to properties of the string it produces and relates it to other string data-structures, allowing it to be studied independently of the CDAWG and providing opportunity for innovation of grammar-based compression algorithms.

关键词： Technological innovation Data compression Grammar compression algorithms

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