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  1. NTU Theses and Dissertations Repository
  2. 電機資訊學院
  3. 資訊工程學系
請用此 Handle URI 來引用此文件: http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/72219
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dc.contributor.advisor周承復
dc.contributor.authorChia-Wei Chienen
dc.contributor.author簡嘉威zh_TW
dc.date.accessioned2021-06-17T06:29:37Z-
dc.date.available2019-08-21
dc.date.copyright2018-08-21
dc.date.issued2018
dc.date.submitted2018-08-16
dc.identifier.citation[1] Heinzelman, W. R., Chandrakasan, A., & Balakrishnan, H. (2000, January). Energy-efficient communication protocol for wireless microsensor networks. In System sciences, 2000. Proceedings of the 33rd annual Hawaii international conference on (pp. 10-pp). IEEE.
[2] Lindsey, S., & Raghavendra, C. S. (2002). PEGASIS: Power-efficient gathering in sensor information systems. In Aerospace conference proceedings, 2002. IEEE (Vol. 3, pp. 3-3). IEEE.
[3] Tang, J., Jiao, X., & Xiao, W. (2013, May). Minimum-latency data aggregation in duty-cycled wireless sensor networks under physical interference model. In Wireless and Optical Communication Conference (WOCC), 2013 22nd (pp. 309-314). IEEE.
[4] Ha, N. P. K., Zalyubovskiy, V., & Choo, H. (2012, October). Delay-efficient data aggregation scheduling in duty-cycled wireless sensor networks. In Proceedings of the 2012 ACM Research in Applied Computation Symposium (pp. 203-208). ACM.
[5] Kang, B., Nguyen, P. K. H., Zalyubovskiy, V., & Choo, H. (2017). A distributed delay-efficient data aggregation scheduling for duty-cycled WSNs. IEEE Sensors Journal, 17(11), 3422-3437.
[6] Chen, Q., Gao, H., Cheng, S., Li, J., & Cai, Z. (2017, May). Distributed non-structure based data aggregation for duty-cycle wireless sensor networks. In INFOCOM 2017-IEEE Conference on Computer Communications, IEEE (pp. 1-9). IEEE.
[7] Nguyen, N. T., Liu, B. H., Pham, V. T., & Liou, T. Y. (2017). An Efficient Minimum-Latency Collision-Free Scheduling Algorithm for Data Aggregation in Wireless Sensor Networks. IEEE Systems Journal.
[8] Tamai, M., & Hasegawa, A. (2017, December). Data aggregation among mobile devices for upload traffic reduction in crowdsensing systems. In Wireless Personal Multimedia Communications (WPMC), 2017 20th International Symposium on (pp. 554-560). IEEE.
[9] Balasubramanya, N. M., Lampe, L., Vos, G., & Bennett, S. (2016). DRX with quick sleeping: A novel mechanism for energy-efficient IoT using LTE/LTE-A. IEEE Internet of Things Journal, 3(3), 398-407.
[10] Ferng, H. W., & Wang, T. H. (2018). Exploring flexibility of DRX in LTE/LTE-A: Design of dynamic and adjustable DRX. IEEE Transactions on Mobile Computing, 17(1), 99-112.
[11] Arunagiri, P., & Nagarajan, G. (2016, January). Optimization of power saving and Latency in LTE network using DRX mechanism. In Intelligent Systems and Control (ISCO), 2016 10th International Conference on (pp. 1-4). IEEE.
[12] Liu, Y., Huynh, M., & Ghosal, D. (2016, February). Enhanced DRX-aware scheduling for mobile users in LTE networks. In Computing, Networking and Communications (ICNC), 2016 International Conference on (pp. 1-5). IEEE.
[13] Herrería-Alonso, S., Rodríguez-Pérez, M., Fernández-Veiga, M., & López-García, C. (2015). Adaptive DRX scheme to improve energy efficiency in LTE networks with bounded delay. IEEE Journal on Selected Areas in Communications, 33(12), 2963-2973.
[14] Khandnor, P. (2017, March). Structure and structure-free data aggregation protocols in wireless sensor networks-a review. In Wireless Communications, Signal Processing and Networking (WiSPNET), 2017 International Conference on (pp. 2136-2140). IEEE.
[15] Lin, K. C. J., Chen, C. W., & Chou, C. F. (2012, March). Preference-aware content dissemination in opportunistic mobile social networks. In INFOCOM, 2012 Proceedings IEEE (pp. 1960-1968). IEEE.
[16] Sasirekha, S., & Swamynathan, S. (2017). Cluster-chain mobile agent routing algorithm for efficient data aggregation in wireless sensor network. Journal of Communications and Networks, 19(4), 392-401.
[17] Sheikhpour, R., Jabbehdari, S., & Khademzadeh, A. (2012). 1 A Cluster-Chain based Routing Protocol for Balancing Energy Consumption in Wireless Sensor Networks.
[18] Wang, L., Wan, P. J., & Young, K. (2015, April). Minimum-Latency Beaconing Schedule in duty-cycled multihop wireless networks. In Computer Communications (INFOCOM), 2015 IEEE Conference on (pp. 1311-1319). IEEE.
[19] Wang, F., & Liu, J. (2012). On reliable broadcast in low duty-cycle wireless sensor networks. IEEE Transactions on Mobile Computing, 11(5), 767-779.
[20] Chen, Q., Cheng, S., Gao, H., Li, J., & Cai, Z. (2015). Energy-efficient algorithm for multicasting in duty-cycled sensor networks. Sensors, 15(12), 31224-31243.
[21] Madden, S., Franklin, M. J., Hellerstein, J. M., & Hong, W. (2002). TAG: A tiny aggregation service for ad-hoc sensor networks. ACM SIGOPS Operating Systems Review, 36(SI), 131-146.
[22] Kang, B., Kwon, N., & Choo, H. (2016). Developing route optimization-based PMIPv6 testbed for reliable packet transmission. IEEE Access, 4, 1039-1049.
[23] http://www.5284.com.tw/Dybus.aspx
[24] http://ibus.tbkc.gov.tw/bus/BusRoute.aspx
dc.identifier.urihttp://tdr.lib.ntu.edu.tw/jspui/handle/123456789/72219-
dc.description.abstract近年來,網路技術不斷在精進,第五代網路的普及亦是指日可待。我們能夠預測到不斷增長的智能自主傳感器以及其對未來世界的影響。然而如今無線感測網路(WSN)在許多領域發揮了重要作用,例如醫療保健,軍事行動,樓房自動化和礦物監測,未來可能會有更多的應用。
在我們的研究中,我們想要解決目前對於大型無線感測網路中資料傳遞方法的缺陷。我們利用類似於無人車的移動點所建構出的車載延遲容忍網路(VDTN)來幫助數個無線感測網路的資料傳遞及整合,使得各個無線感測網路只需要如期醒來並且將資料傳遞給附近的移動點,省去原本在感測網路中許多耗電的程序而延長其壽命,讓感測器能夠將僅存的電力全部用在感測資料上。而我們的方法亦能讓無線感測網路之間能夠獨立的運作不會因為方法的設計而互相影響,進而減少不必要的能源耗損。我們對此提出一個完善的方法,而經由實驗模擬結果顯示我們的方法能有效提升資料的匯合度使減輕基地台的負載量,同時亦減少平均上傳資料的距離而降低訊號碰撞的程度。
zh_TW
dc.description.abstractIn recent years, network technology has continued to improve, and the popularity of fifth-generation networks is just around the corner. We are able to anticipate the growing intelligence of autonomous sensors and their impact on the future world. Nowadays, wireless sensor networks (WSNs) play an important role in many fields, such as healthcare, military operations, building automation and mineral monitoring, and there may be more applications in the future.
In our research, we want to address the shortcomings of current data collecting methods for wireless sensor networks in smart city. We use the Vehicular Delay Tolerant Networks (VDTN) built by unmanned vehicles to help with the data collecting and aggregating of several WSNs, so that a wireless sensor network only needs to wake up and send the aggregated data to unmanned vehicles nearby it to eliminate lots of power-consuming processes such as communicating with other WSNs, allowing the sensors to use all of the remaining power for sensing data. Our approach also enables independent operation of wireless sensing networks without interfering each other caused by the design of the method, thereby reducing unnecessary energy consumption. We propose a method for these goals, and the experimental simulation results show that our method can effectively improve the aggregation of sensors’ data to reduce the load of the base stations, and also reduce the average distance of uploading data and then reduce the potentially signal collisions.
en
dc.description.provenanceMade available in DSpace on 2021-06-17T06:29:37Z (GMT). No. of bitstreams: 1
ntu-107-R05922113-1.pdf: 2796303 bytes, checksum: 07137726cbd20c7d0f46aa348920339d (MD5)
Previous issue date: 2018
en
dc.description.tableofcontentsCONTENTS
誌謝 .................................................i
摘要 .................................................ii
ABSTRACT .................................................iii
LIST OF FIGURES .................................................vi
LIST OF TABLES .................................................vii
Chapter 1 Introduction ................................. 1
Chapter 2 Related Work ................................. 6
Chapter 3 System Model ................................. 8
3.1 Scenario ......................................... 8
3.2 Problem Formulation .................................11
3.2.1 How to Decide the Sender and Receiver? .12
3.2.2 When to Upload Data? ......................13
Chapter 4 Methodology .................................14
4.1 Sensor’s Self-Adjusting Mechanism .................14
4.2 Mobile Node’s Contribution Quantification .........16
4.2.1 Mobile Node’s Scheduled Uploading Time .16
4.2.2 Sender & Receiver Decision .................17
Chapter 5 Evaluation .................................20
5.1 Simulation Scenario .................................20
5.2 Performance .......................................24
5.2.1 Aggregation Ratio .........................25
5.2.2 Average Uploading Distance .................27
5.2.3 Total Power Consumption for Uploading Data .27
5.3 The Influence of Different Value of Parameters .30
5.3.1 The Length of Sub-Period .................30
5.3.2 The Length of Threshold .................32
5.3.3 The Period of Hello Packet .................34
Chapter 6 Conclusion .................................37
REFERENCE .................................................38
dc.language.isoen
dc.subject車載延遲容忍網路zh_TW
dc.subject無線感測網路zh_TW
dc.subject資料聚合zh_TW
dc.subjectVehicular Delay Tolerant Networksen
dc.subjectWireless Sensor Networken
dc.subjectdata aggregationen
dc.title使用具有社群網路特性的移動節點進行無線感測網路的資料聚合zh_TW
dc.titleUsing Mobile Nodes with Social Network Feature for Data Aggregation in Wireless Sensor Networken
dc.typeThesis
dc.date.schoolyear106-2
dc.description.degree碩士
dc.contributor.oralexamcommittee吳曉光,林俊宏,蔡子傑
dc.subject.keyword車載延遲容忍網路,資料聚合,無線感測網路,zh_TW
dc.subject.keywordVehicular Delay Tolerant Networks,data aggregation,Wireless Sensor Network,en
dc.relation.page40
dc.identifier.doi10.6342/NTU201802622
dc.rights.note有償授權
dc.date.accepted2018-08-17
dc.contributor.author-college電機資訊學院zh_TW
dc.contributor.author-dept資訊工程學研究所zh_TW
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