The pervasiveness of GPS-enabled devices and wireless communication technologies results in massive trajectory data, incurring expensive cost for storage, transmission, and query processing. To relieve this problem, i...
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ISBN:
(纸本)9781450355520
The pervasiveness of GPS-enabled devices and wireless communication technologies results in massive trajectory data, incurring expensive cost for storage, transmission, and query processing. To relieve this problem, in this paper we propose a novel framework for compressing trajectory data, REST (Reference-based Spatio-temporal trajectory compression), by which a raw trajectory is represented by concatenation of a series of historical (sub-)trajectories (called reference trajectories) that form the compressed trajectory within a given spatio-temporal deviation threshold. In order to construct a reference trajectory set that can most benefit the subsequent compression, we propose three kinds of techniques to select reference trajectories wisely from a large dataset such that the resulting reference set is more compact yet covering most footprints of trajectories in the area of interest. To address the computational issue caused by the large number of combinations of reference trajectories that may exist for resembling a given trajectory, we propose efficient greedy algorithms that run in the blink of an eye and dynamic programming algorithms that can achieve the optimal compression ratio. Compared to existing work on trajectory compression, our framework has few assumptions about data such as moving within a road network or moving with constant direction and speed, and better compression performance with fairly small spatio-temporal loss. Extensive experiments on a real taxi trajectory dataset demonstrate the superiority of our framework over existing representative approaches in terms of both compression ratio and efficiency.
Data compression plays an important role in lesser expensive resource consumption. It is also cumbersome to send a huge amount of data through the network. The data compression techniques help in optimizing physical s...
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ISBN:
(纸本)9781728196008
Data compression plays an important role in lesser expensive resource consumption. It is also cumbersome to send a huge amount of data through the network. The data compression techniques help in optimizing physical storage devices as well as it makes easy to transfer the compressed data or file faster through internet or network. Deoxyribonucleic acid or DNA is biological traits presents in human and almost all other living organisms. The DNA contains the genetic information of the living organisms. In this research, various compression algorithms for DNA sequences are studied and compared. The scheme proposed here for compression is the use of a burrows wheeler compression technique. Our proposed algorithm is the modification of the Burrows Wheeler compression algorithm (BWCA). The lexicographical sorting of the matrix is replaced by the polynomial base representation of the bases of DNA. This method reduces the time for compression positively. Validation was performed on various datasets that concur the efficiency of the proposed scheme.
The escalation of the Internet of Things applications has put on display the different sensor data processing methods. The sensor data compression is one of the fundamental methods to reduce the amount of data needed ...
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ISBN:
(纸本)9781728169972
The escalation of the Internet of Things applications has put on display the different sensor data processing methods. The sensor data compression is one of the fundamental methods to reduce the amount of data needed to transmit from the sensor node which is often battery powered and operates wirelessly. Reducing the amount of data in wireless transmission is an effective way to reduce overall energy consumption in wireless sensor nodes. The methods presented and tested are suitable for constrained sensor nodes with limited computational power and limited energy resources. The methods presented are compared with each other using compression ratio and inherent latency. Latency is an important parameter in on-line applications. The improved variation of the linear regression-based method called RT-LRbTC is tested and it has proved to be a potential method to be used in a wireless sensor node with a fixed and predictable latency. The compression efficiency of the compression algorithms is tested with real measurement data sets.
In the paper, the method of data preprocessing by segmentation procedure needed for increasing efficiency of compressing is offered. The basic principle of segmentation procedure of input data sequence is described an...
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ISBN:
(纸本)9781479971039
In the paper, the method of data preprocessing by segmentation procedure needed for increasing efficiency of compressing is offered. The basic principle of segmentation procedure of input data sequence is described and the data compression algorithm is offered. The efficiency of proposed method as data compression procedure and also as data preprocessing procedure before using of some compression algorithm is shown.
Burrows-Wheeler Transform (BWT) is a new data transform method, firstly introduced by Burrows and Wheeler in 1994 and used in a lossless data compression algorithm. In the original version of data compression algorith...
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ISBN:
(纸本)9780769551340
Burrows-Wheeler Transform (BWT) is a new data transform method, firstly introduced by Burrows and Wheeler in 1994 and used in a lossless data compression algorithm. In the original version of data compression algorithm based on BWT, Burrows and Wheeler used the Move-To-Front (MTF) transform after the BWT and entropy coding (Huffman coding) for encoding the transform result in the last stage. Ferragina and Manzini combined the compression algorithm based on BWT and the suffix array data structure, and proposed a new opportunistic data structure. They shortly called it FM-index in that it is a Full-text index and occupies Minute space. This paper mainly describes the methods about compression and index based on BWT, and relationship between them. At last, the paper compares some tools.
Edge computing is currently one of the main research topics in the field of Internet of Things. Edge computing requires lightweight and computationally simple algorithms for sensor data analytics. Sensing edge devices...
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ISBN:
(纸本)9783030308599;9783030308582
Edge computing is currently one of the main research topics in the field of Internet of Things. Edge computing requires lightweight and computationally simple algorithms for sensor data analytics. Sensing edge devices are often battery powered and have a wireless connection. In designing edge devices the energy efficiency needs to be taken into account. Pre-processing the data locally in the edge device reduces the amount of data and thus decreases the energy consumption of wireless data transmission. Sensor data compression algorithms presented in this paper are mainly based on data linearity. Microclimate data is near linear in short time window and thus simple linear approximation based compression algorithms can achieve rather good compression ratios with low computational complexity. Using these kind of simple compression algorithms can significantly improve the battery and thus the edge device lifetime. In this paper linear approximation based compression algorithms are tested to compress microclimate data.
Due to the popularity of online repositories, an efficient compression algorithm that removes statistical redundancy and psychovisual redundancies without perceptual degradation is important for data transmission and ...
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ISBN:
(纸本)9781457719219
Due to the popularity of online repositories, an efficient compression algorithm that removes statistical redundancy and psychovisual redundancies without perceptual degradation is important for data transmission and storage. Visual attention model and visual sensitivity model are proposed for removing psychovisual redundancies. However most visual attention models are based on spatial component analysis, and only a few adopt motion vectors for temporal component analysis, which lacks perceptual information. This paper proposes a scene motion and saliency motion based visual attention model that effectively traces the movement of salient regions, and incorporates the obtained motion saliency map with Just Noticeable Distortion (JND) to determine the quantization parameters. The proposed framework achieves an 8% to 73% bit rate reduction compared with the H. 264 in version JM14.0, and its bit rate reduction is three times higher than the previous methods. Visual quality assessment experiments indicate that participants cannot distinguish the difference between the compressed video streams and the original video streams.
JPEG2000 is the latest ISO/IEC standard for still image coding. Its core part has already been published as an international standard (IS), and work on its subsequent parts is under way. In this paper author's enc...
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ISBN:
(纸本)9537044025
JPEG2000 is the latest ISO/IEC standard for still image coding. Its core part has already been published as an international standard (IS), and work on its subsequent parts is under way. In this paper author's encoder implementation compliant with core part of JPEG2000 will be presented, as well as results of comparison between presented JPEG2000 encoder implementation and two publicly available JPEG and JPEG-LS implementations. Also, main features of JPEG2000 standard in comparison to somewhat older JPEG and JPEG-LS international standards will be briefly described.
compression techniques have a vital role to minimize the cost of information storage and/or transmission. In particular, techniques of image compression make the use of visual perception and statistical properties of ...
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An executable file compression solution for mobile terminals of MIS was proposed, optimal compression algorithm was selected and ported to BREW platform. Meanwhile, concrete implementation of this proposal was given. ...
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ISBN:
(纸本)9781424453023
An executable file compression solution for mobile terminals of MIS was proposed, optimal compression algorithm was selected and ported to BREW platform. Meanwhile, concrete implementation of this proposal was given. Experiment results on mobile terminals using Arm7 chip show that, under the premise of guaranteeing the running speed of the application, this solution with strong practicability can reduce the executable file size to 35 similar to 55 percents of its origin, which has a significant savings in storage capacity of mobile phones on CDMA platform, and has greatly reduced the network transmission time of the executable file.
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