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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 謝宏昀(Hung-Yun Hsieh) | |
dc.contributor.author | Wei-Chih Liao | en |
dc.contributor.author | 廖偉志 | zh_TW |
dc.date.accessioned | 2021-06-16T08:47:46Z | - |
dc.date.available | 2014-08-26 | |
dc.date.copyright | 2013-08-26 | |
dc.date.issued | 2013 | |
dc.date.submitted | 2013-08-20 | |
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dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/59064 | - |
dc.description.abstract | 物聯通訊的一大特色是裝置數量龐大,並具有大量資料傳輸的需求。不同於一
般網路下考慮如何去最佳化每個個別物聯裝置的效能,我們根據「大量資料」難 以完整蒐集的特性,試圖著眼於如何利用有限的資源來盡可能地蒐集到最多的有 用資訊,並引入對於資料相關性的探討從而提升整體網路的效能。對於此一類問 題,過去相關文獻中常利用分散式的編碼,利用資料間的相關性來減少資料量及 資源的消耗,但其相對代價是整體設計上複雜度的提升和額外資源的使用,因此 本論文提出一根據每個物聯裝置所側聽到的資訊從而作編碼並去除相關資料的技 術,此一技術之優點在於其不需要事先資訊的交換,也因此可以減輕系統負擔。 為探討在此一技術架構下的特性,我們首先提出一混和傳輸點選擇與排程規劃的 最佳化問題,並將此問題拆解成「支援傳輸點選擇」的子問題以及「資源可行性 檢測」兩子問題,利用交叉熵值法(Cross Entropy Method)與所提出的排程規劃技 術結合而成的演算法以解決此問題。另外在側聽機制下,隱含了一每個物聯裝置 利用額外資源以擴大傳輸範圍以幫助它人節省相關資料的可能,在所討論的問題 裡此一可能性也被納入作更深入的考量。透過電腦模擬與數據分析,可發現我們 提出的演算法相較於分散式編碼有較低的複雜度,並且即使在側聽範圍與時間上 有所受限的情況下,相對於獨立編碼亦能收得良好的效能且接近分散式編碼,相 較於以個別物聯通訊服務為考量的資源分配,當資料相關性高時在資訊蒐集上 能有近35%的增幅。此外,我們也注意到物聯網下因為物聯裝置電池的不可充電 性,能量使用亦是個重要的議題。根據我們前述所建立的模型,我們進一步地討 論如何在確保基地台蒐集到需要資料量的情況下,同時能減少網路資源的使用, 以期能有效地延長整體網路壽命。我們將原方法做延伸,在傳輸點選擇時同時考 量剩餘能量的因素以更平衡整體網路負載。透過電腦模擬顯示,我們此種以資料 特性與資料相關性作探討的觀點,確實能更妥善地利用頻譜之空間並達到網路生 命的延長。 | zh_TW |
dc.description.abstract | Many applications involving machine-to-machine (M2M) communications are characterized by large amount of data to transport. To address the big data problem introduced by M2M applications, we argue that instead of focusing on better
serving individual machines, we take into consideration useful information content of the correlated data for resource allocation and aim to maximize the information from the data. Unlike related work that employs distributed source coding for minimizing resource usage, we assume that machines are able to perform dependent source coding based on data overheard from transmissions of others to reduce the redundancy, and cost for exchange of data correlation knowledge is unnecessary under the scheme. To explore the performance tradeo s of overhearing, we formulate a joint optimization problem involving node selection, resource allocation, and transmission scheduling with proposed solution. With the potential bene ts from enlarging transmission range to make others heard, we further discuss the range expansion scheme to optimize the resource usage. Evaluation results show that without incurring the complexity of distributed source coding, dependent source coding via overhearing can achieve noticeable performance gain even if the overhearing range and time are limited. Furthermore, energy consumption plays an important role for the performance due to the non-rechargeable property. We thus focus on extending the network lifetime for future application, while ensure the data collection tting the application requirement by exploiting the correlation for data reconstruction. We aim to prolong the time when the network cannot achieve the required delity with given resource, and results show that for data-centric resource allocation, it can achieve better performance than machine-centric approaches in prolonging network lifetime. | en |
dc.description.provenance | Made available in DSpace on 2021-06-16T08:47:46Z (GMT). No. of bitstreams: 1 ntu-102-R00942047-1.pdf: 5007294 bytes, checksum: 0f16e19b4cd9806fc6aab72f4602c52e (MD5) Previous issue date: 2013 | en |
dc.description.tableofcontents | ABSTRACT ii
LIST OF FIGURES v LIST OF ALGORITHMS vi CHAPTER 1 INTRODUCTION 1 CHAPTER 2 BACKGROUND AND RELATED WORK 4 2.1 Network Model 4 2.1.1 Data Source Model 5 2.1.2 Data Correlation Model 5 2.1.3 Data Compression Model 6 2.1.4 Resource Allocation 7 2.1.5 Data Centric 8 2.2 Related Work 10 CHAPTER 3 RESOURCE ALLOCATION UNDER DEPENDENT SOURCE CODING 14 3.1 Problem and Motivation 14 3.1.1 Motivation 15 3.1.2 Problem Formulation 16 3.2 Transmission Scheduling Sub-Problem 18 3.3 An Algorithm for Transmission Scheduling 22 3.3.1 A Stochastic Algorithm Based on Cross Entropy 26 3.3.2 Resource Allocation for Range Expansion 28 3.4 Evaluation 32 3.5 Summary 42 CHAPTER 4 RESOURCE ALLOCATION FOR RESOURCE CONSERVATION 43 4.1 Problem Formulations under Distortion Measure 43 4.1.1 Distortion Measure 44 4.1.2 Minimizing Resource Problem 45 4.1.3 Solution Algorithm 47 4.2 Network Lifetime Extension 48 4.2.1 Motivation for the Work 49 4.2.2 Network Lifetime Issue 49 4.2.3 Transmission Power Control 52 4.3 Evaluation 54 4.4 Summary 60 CHAPTER 5 CONCLUSION AND FUTURE WORK 62 5.1 Conclusion 62 5.2 Future Work 63 REFERENCES 64 | |
dc.language.iso | en | |
dc.title | 物聯通訊下基於側聽編碼之資源分配與排程技術 | zh_TW |
dc.title | Leveraging Overhearing for Correlated Data Gathering in Machine-to-Machine Wireless Networks | en |
dc.type | Thesis | |
dc.date.schoolyear | 101-2 | |
dc.description.degree | 碩士 | |
dc.contributor.oralexamcommittee | 趙禧綠(Hsi-Lu Chao),葉書蘋(Shu-Ping Yeh) | |
dc.subject.keyword | 分散式編碼,側聽編碼,傳輸點選擇,資源分配,傳輸排程, | zh_TW |
dc.subject.keyword | Slepian-Wolf coding,transmission overhearing,node selection,resource allocation,transmission scheduling, | en |
dc.relation.page | 67 | |
dc.rights.note | 有償授權 | |
dc.date.accepted | 2013-08-20 | |
dc.contributor.author-college | 電機資訊學院 | zh_TW |
dc.contributor.author-dept | 電信工程學研究所 | zh_TW |
顯示於系所單位: | 電信工程學研究所 |
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