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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 張瑞益(Ray-I Chang) | |
| dc.contributor.author | Yu-Wei Lee | en |
| dc.contributor.author | 李育瑋 | zh_TW |
| dc.date.accessioned | 2021-06-17T06:23:03Z | - |
| dc.date.available | 2018-08-21 | |
| dc.date.copyright | 2018-08-21 | |
| dc.date.issued | 2018 | |
| dc.date.submitted | 2018-08-17 | |
| dc.identifier.citation | [1] DASGUPTA, Koustuv; KALPAKIS, Konstantinos; NAMJOSHI, Parag. An efficient clustering-based heuristic for data gathering and aggregation in sensor networks. In: Wireless Communications and Networking, 2003. WCNC 2003. 2003 IEEE. IEEE, 2003. p. 1948-1953.
[2] LIANG, Yao; PENG, Wei. Minimizing energy consumption in wireless sensor networks via two-modal transmission. ACM SIGCOMM Computer Communication Review, 2010, 40.1: 12-18. [3] AKYILDIZ, Ian F., et al. Wireless sensor networks: a survey. Computer networks, 2002, 38.4: 393-422. [4] KIMURA, Naoto; LATIFI, Shahram. A survey on data compression in wireless sensor networks. In: International Conference on Information Technology: Coding and Computing (ITCC'05)-Volume II. IEEE, 2005. p. 8-13. [5] STANDARD, ASHRAE. Standard 41.1-1986, 1986,“Standard Method for Temperature Measurement,”. American Society of Heating, Refrigerating and Air-Conditioning Engineers, Inc., Atlanta, GA. [6] 蔡坤成. 織造製程品質提升與染色優化創新技術發展. 電工通訊季刊, 2016, 78-84. [7] SHARAF, Mohamed A., et al. TiNA: a scheme for temporal coherency-aware in-network aggregation. In: Proceedings of the 3rd ACM international workshop on Data engineering for wireless and mobile access. ACM, 2003. p. 69-76. [8] 林哲論. 有限誤差霍夫曼編碼在無線感測網路的資料壓縮應用. 臺灣大學工程科學及海洋工程學研究所學位論文, 2014, 1-57. [9] CHEN, Yu-Hao, et al. Dynamic bounded-error data compression and aggregation in wireless sensor network. In: Sensors, 2012 IEEE. IEEE, 2012. p. 1-4. [10] LIN, Che-Lung, et al. Concept of bounded error to improve wireless sensor network data compression. In: SENSORS, 2014 IEEE. IEEE, 2014. p. 1240-1243. [11] LI, Meng-Han, et al. Error-bounded data compression using data, temporal and spatial correlations in wireless sensor networks. In: Multimedia Information Networking and Security (MINES), 2010 International Conference on. IEEE, 2010. p. 111-115. [12] TSAI, Jui-Hua. 無線感測網路之有限誤差線上查詢處理. 臺灣大學工程科學及海洋工程學研究所學位論文, 2015, 1-48. [13] AGARWAL, Sameer, et al. BlinkDB: queries with bounded errors and bounded response times on very large data. In: Proceedings of the 8th ACM European Conference on Computer Systems. ACM, 2013. p. 29-42. [14] HELLERSTEIN, Joseph M.; HAAS, Peter J.; WANG, Helen J. Online aggregation. In: ACM SIGMOD Record. ACM, 1997. p. 171-182. [15] FERILLI, Stefano. Automatic digital Document processing and management: Problems, algorithms and techniques. Springer Science & Business Media, 2011. [16] KAWAHARA, Mikio; CHIU, Yi-Jen; BERGER, Toby. High-speed software implementation of Huffman coding. In: Data Compression Conference, 1998. DCC'98. Proceedings. IEEE, 1998. p. 553. [17] IBRAHIM, Amin Mubark Alamin; MUSTAFA, Mustafa Elgili. Comparison Between (RLE And Huffman) Algorithms for Lossless Data Compression. IJITR, 2015, 3.1: 1808-1812. [18] XIA, Feng, et al. Internet of things. International Journal of Communication Systems, 2012, 25.9: 1101. [19] BOUBRIMA, Ahmed; BECHKIT, Walid; RIVANO, Hervé. Error-Bounded Air Quality Mapping Using Wireless Sensor Networks. In: Local Computer Networks (LCN), 2016 IEEE 41st Conference on. IEEE, 2016. p. 380-388. [20] LONG, Shengchun; XIANG, Pengyuan. Lossless Data Compression for Wireless Sensor Networks Based on Modified Bit-Level RLE. In: Wireless Communications, Networking and Mobile Computing (WiCOM), 2012 8th International Conference on. IEEE, 2012. p. 1-4. [21] ARICI, Tarik, et al. PINCO: A pipelined in-network compression scheme for data collection in wireless sensor networks. In: Computer Communications and Networks, 2003. ICCCN 2003. Proceedings. The 12th International Conference on. IEEE, 2003. p. 539-544. [22] MASTRIANI, Mario. Single frame supercompression of still images, video, High Definition TV and Digital Cinema. International Journal of Engineering and Mathematical Sciences, 2010, 6.3: 146-162. | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/72094 | - |
| dc.description.abstract | 隨著物聯網(Internet-of-Things, IoT)的應用日漸興起，與其相關的無線感測網路(Wireless Sensor Networks, WSN)使用研究也日益顯得重要。由於物聯網之節點大多配置在無線環境，且不易供電，如何降低節點耗電量來延長生命週期便成為一個很重要的研究議題，而物聯網節點主要之行為可以分為資料感測、資料運算及資料傳輸，其中又以資料傳輸最為耗電，也因此成為主要的研究目標。本研究以有限誤差壓縮的方式，透過容許一定量的誤差，將近似的數值視為相同，進而使得傳輸量減少，最終達到壓縮的目的。此外我們也以紡織機台數據為資料集，在實驗中比較了Bounded-Error Run-Length Encoding (BERLE)與Bounded-Error Huffman Coding (BEHC)兩種演算法在邊界運算(Edge Computing)閘道器上的實際壓縮效果。 | zh_TW |
| dc.description.abstract | With the application of internet-of-things (IoT) has become more popular, research about using wireless sensor networks (WSN) has also become more important. Due to the nodes in IoT usually set up in the wireless environment, difficult to supply power, how to reduce consumption to extend the lifetime becomes a significant issue. The main behavior of the nodes in IoT are data sensing, data operation, data transmission. Among above, data transmission always takes the largest part of sensors’ power consumption. Thus, data transmission becomes on main study. In this thesis, we use a way of bounded-error compression by allowing certain amount of errors, regarding similar value as the same. Thus reduce the amount of data transmission and finally achieve the compression. In addition, we also use the textile machine data set to compare the actual compression on edge computing gateway with Bounded-Error Run-Length Encoding (BERLE) and Bounded-Error Huffman Coding (BEHC) in the experiment. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-17T06:23:03Z (GMT). No. of bitstreams: 1 ntu-107-R03525097-1.pdf: 1368829 bytes, checksum: 0eda427e29241020ef8a54a96b05d051 (MD5) Previous issue date: 2018 | en |
| dc.description.tableofcontents | 口試委員會審定書 #
誌謝 i 中文摘要 ii ABSTRACT iii CONTENTS iv 圖目錄 vi 表目錄 vii Chapter 1 簡介 1 Chapter 2 文獻探討 4 2.1 Run Length Encoding 4 2.2 Huffman Coding 5 2.3 有限誤差 6 2.4 物聯網系統 7 2.5 多功能智慧閘道器AEG-200簡介 9 Chapter 3 實驗 11 3.1 方法 11 3.1.1 Bounded-Error Run-length Encoding (BERLE) 11 3.1.2 Bounded-Error Huffman Coding (BEHC) 13 3.2 資料集 16 3.3 實驗架構 18 Chapter 4 實驗結果 20 Chapter 5 結論 34 REFERENCES 35 | |
| dc.language.iso | zh-TW | |
| dc.subject | 物聯網 | zh_TW |
| dc.subject | 邊界運算 | zh_TW |
| dc.subject | 閘道器 | zh_TW |
| dc.subject | 有限誤差 | zh_TW |
| dc.subject | 壓縮 | zh_TW |
| dc.subject | 紡織機台資料 | zh_TW |
| dc.subject | Compression | en |
| dc.subject | IoT | en |
| dc.subject | Edge Computing | en |
| dc.subject | Gateway | en |
| dc.subject | Textile Machine Data | en |
| dc.subject | Bounded-error | en |
| dc.title | 有限誤差壓縮在閘道器上之應用 | zh_TW |
| dc.title | Application of Bounded-error Compression on Industrial Gateway | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 106-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 丁肇隆,張恆華,王家輝 | |
| dc.subject.keyword | 物聯網,邊界運算,閘道器,有限誤差,壓縮,紡織機台資料, | zh_TW |
| dc.subject.keyword | IoT,Edge Computing,Gateway,Bounded-error,Compression,Textile Machine Data, | en |
| dc.relation.page | 37 | |
| dc.identifier.doi | 10.6342/NTU201803921 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2018-08-18 | |
| dc.contributor.author-college | 工學院 | zh_TW |
| dc.contributor.author-dept | 工程科學及海洋工程學研究所 | zh_TW |
| 顯示於系所單位： | 工程科學及海洋工程學系 | |
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| ntu-107-1.pdf 未授權公開取用 | 1.34 MB | Adobe PDF |
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