請用此 Handle URI 來引用此文件:
http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/37265完整後設資料紀錄
| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 黃寶儀(Polly Huang) | |
| dc.contributor.author | Tsung-Han Lin | en |
| dc.contributor.author | 林宗翰 | zh_TW |
| dc.date.accessioned | 2021-06-13T15:22:53Z | - |
| dc.date.available | 2010-07-30 | |
| dc.date.copyright | 2008-07-30 | |
| dc.date.issued | 2008 | |
| dc.date.submitted | 2008-07-23 | |
| dc.identifier.citation | [1] Chipcon: CC2420 802.15.4 compliant radio. http://www.chipcon.com.
[2] ADXL202 datasheet. http://www.analog.com/, October 2000. [3] ADXL330 datasheet. http://www.analog.com/, September 2006. [4] P. Bahl and V. N. Padmanabhan. Radar: An in-building rf-based user location and tracking system. In INFOCOM, pages 775–784, 2000. [5] S. Basagni, I. Chlamtac, V. R. Syrotiuk, and B. A. Woodward. A distance routing effect algorithm for mobility (dream). In MOBICOM, pages 76–84, 1998. [6] M. A. Batalin, M. H. Rahimi, Y. Yu, D. Liu, A. Kansal, G. S. Sukhatme, W. J. Kaiser, M. M. Hansen, G. J. Pottie, M. B. Srivastava, and D. Estrin. Call and response: experiments in sampling the environment. In SenSys, pages 25–38, 2004. [7] A. Bhattacharya and S. K. Das. Lezi-update: an information-theoretic framework for personal mobility tracking in pcs networks. Wirel. Netw., 8(2/3):121–135, 2002. [8] L. Breslau, D. Estrin, K. R. Fall, S. Floyd, J. S. Heidemann, A. Helmy, P. Huang, S. McCanne, K. Varadhan, Y. Xu, and H. Yu. Advances in network simulation. IEEE Computer, 33(5):59–67, 2000. [9] Z. J. Butler, P. I. Corke, R. A. Peterson, and D. Rus. Virtual fences for controlling cows. In ICRA, pages 4429–4436, 2004. [10] A. P. Chandrakasan and R. W. Brodersen. Low Power Digital CMOS Design. Kluwer Academic Publisher, 1995. [11] L. Cong andW. Zhuang. Hybrid tdoa/aoa mobile user location for wideband cdma cellular systems. Wireless Communications, IEEE Transactions on, 1(3):439–447, Jul 2002. [12] G. Debunne, M. Desbrun, M.-P. Cani, and A. H. Barr. Dynamic real-time deformations using space & time adaptive sampling. In SIGGRAPH, pages 31–36, 2001. [13] L. M. Feeney. An energy consumption model for performance analysis of routing protocols for mobile ad hoc networks. Mob. Netw. Appl., 6(3):239–249, 2001. [14] R. Harle and A. Hopper. The potential for location-aware power management. In Ubicomp, 2008. [15] M. Hazas, J. Scott, and J. Krumm. Location-aware computing comes of age. IEEE Computer, 37(2):95–97, 2004. [16] J. Hightower and G. Borriello. Particle filters for location estimation in ubiquitous computing: A case study. In Ubicomp, pages 88–106, 2004. [17] D. Johnson and D. Maltz. Dynamic source routing in ad hoc wireless networks. Mobile Computing, 353:153–181, 1996. [18] C. E. Jones, K. M. Sivalingam, P. Agrawal, and J.-C. Chen. A survey of energy efficient network protocols for wireless networks. Wireless Networks, 7(4):343–358, 2001. [19] M. B. Kjærgaard, G. Treu, and C. Linnhoff-Popien. Zone-based RSS reporting for location fingerprinting. In Pervasive, pages 316–333, 2007. [20] S.-W. Lee and K. Mase. Incremental motion-based location recognition. In ISWC, pages 123–, 2001. [21] K. Lorincz and M. Welsh. MoteTrack: a robust, decentralized approach to RF-based location tracking. Personal Ubiquitous Comput., 11(6):489–503, 2007. [22] D. Madigan, E. Einahrawy, R. P. Martin, W.-H. Ju, P. Krishnan, and A. S. Krishnakumar. Bayesian indoor positioning systems. In INFOCOM, pages 1217–1227, 2005. [23] D. Niculescu. Positioning in ad hoc sensor networks. IEEE Network, 18(4):24–29, 2004. [24] N. Patwari, I. Hero, A.O., M. Perkins, N. Correal, and R. O’Dea. Relative location estimation in wireless sensor networks. Signal Processing, IEEE Transactions on [see also Acoustics, Speech, and Signal Processing, IEEE Transactions on], 51(8):2137–2148, Aug. 2003. [25] J. Polastre, R. Szewczyk, and D. E. Culler. Telos: enabling ultra-low power wireless research. In IPSN, pages 364–369, 2005. [26] N. B. Priyantha, A. Chakraborty, and H. Balakrishnan. The cricket location-support system. In MOBICOM, pages 32–43, 2000. [27] V. Raghunathan, S. Ganeriwal, and M. Srivastava. Emerging techniques for long lived wireless sensor networks. Communications Magazine, IEEE, 44(4):108–114, 2006. [28] N. Ravi, P. Shankar, A. Frankel, A. Elgammal, and L. Iftode. Indoor localization using camera phones. In WMCSA ’06: Proceedings of the Seventh IEEE Workshop on Mobile Computing Systems & Applications: Supplement, pages 1–7, Washington, DC, USA, 2006. IEEE Computer Society. [29] S. Singh and C. S. Raghavendra. Pamas—power aware multi-access protocol with signalling for ad hoc networks. SIGCOMM Comput. Commun. Rev., 28(3):5–26, 1998. [30] K. M. Sivalingam, J.-C. Chen, P. Agrawal, and M. B. Srivastava. Design and analysis of low-power access protocols for wireless and mobile atm networks. Wirel. Netw., 6(1):73– 87, 2000. [31] G. Wan and E. C. Lin. A dynamic paging scheme for wireless communication systems. In MOBICOM, pages 195–203, 1997. [32] Y. Xu, J. Winter, and W.-C. Lee. Prediction-based strategies for energy saving in object tracking sensor networks. In Mobile Data Management(MDM), pages 346–357, 2004. [33] K. Yedavalli, B. Krishnamachari, S. Ravula, and B. Srinivasan. Ecolocation: a sequence based technique for rf localization in wireless sensor networks. In IPSN, pages 285–292, 2005. [34] S.-Y. Yeh, K.-H. Chang, C.-I. Wu, H.-H. Chu, and J. Y.-J. Hsu. Geta sandals: a footstep location tracking system. Personal Ubiquitous Comput., 11(6):451–463, 2007. [35] M. Youssef and A. K. Agrawala. Handling samples correlation in the horus system. In INFOCOM, 2004. | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/37265 | - |
| dc.description.abstract | 邊界偵測是一種用於偵測追蹤目標是否進入重要區域的位置感知服務。定位時運用較低的位置更新速度,通常可降低系統耗電量,但同時也犧牲了偵測事件的即時性及準確度。在此篇論文中,我們提出根據目標移動狀況,而動態調整定位更新速度的機制,以降低系統耗電量並維持系統偵測的準確度。在模擬測試及在實體測試平台的結果均顯示我們所提出之機制在不影響系統準確度的前提下,可有效減少系統耗電量。值得一提的是,運用實際量測的定位誤差的測試結果,更顯示系統耗電量可有效減少20%。 | zh_TW |
| dc.description.abstract | Boundary detection is a form of location-aware services that aims at detecting targets crossing certain critical regions. Typically, a lower location sampling rate contributes to a lower level of energy consumption but, in the meantime, delays the detection of boundary crossing events. Opting to enable energy-efficient boundary detection services, we propose a mobility-aware mechanism that adapts the location sampling rate to the target mobility. Results from our simulations and live experiments confirm that the proposed adaptive sampling mechanism is effective. In particular, when experimented with realistic errors measured from a live RF-based localization system, the energy consumption can be reduced significantly to 20%. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-13T15:22:53Z (GMT). No. of bitstreams: 1 ntu-97-R95921119-1.pdf: 710302 bytes, checksum: 24ba577220bbfe256b5cd4f44ca8ba7f (MD5) Previous issue date: 2008 | en |
| dc.description.tableofcontents | 誌謝 ii
摘要 iii Abstract iv List of Figures vii List of Tables viii Chapter 1 Introduction 1 Chapter 2 Mobility-Aware Sampling Mechanism 5 2.1 Basic Scheme . . . . . . . . . . . . . . . . . 6 2.2 Extended Scheme . . . . . . . . . . . . . . . .7 Chapter 3 Simulation 9 3.1 Simulation Settings . . . . . . . . . . . . . 10 3.2 Performance Metrics . . . . . . . . . . . . . 11 3.3 Results without Localization Error . . . . . .12 3.4 Results with Localization Error . . . . . . . 14 3.5 Gain of Mobility-Aware Sampling . . . . . . . 16 3.6 Impact of Mobility . . . . . . . . . . . . . .18 3.7 Impact of Boundary Crossing Rate . . . . . . .21 Chapter 4 Implementation 24 4.1 System Implementation . . . . . . . . . . . . 24 4.2 Experimental Settings . . . . . . . . . . . . 26 4.3 Experimental Results . . . . . . . . . . . . .27 Chapter 5 Related Work 30 5.1 Mobility-Aware Communication Systems . . . . .30 5.2 Adaptive Sampling . . . . . . . . . . . . . . 32 5.3 Location Estimation Techniques . . . . . . . .33 5.4 Energy-Efficient Designs . . . . . . . . . . .34 Chapter 6 Conclusion and Future Work 36 Bibliography 37 List of Figures 1.1 System Architecture 3 2.1 Illustration of Mobility-Aware Sampling 6 3.1 Results Without Localization Error 13 3.2 Results With Localization Error 15 3.3 Comparison of No-Error and RF-Error Case 17 3.4 Reduction of Location Sampling Rate 18 3.5 Impact of Mobility on Sampling Rate 19 3.6 Impact of Mobility on Detection Accuracy 19 3.7 Impact of Boundary Crossing Rate on Sampling Rate 23 3.8 Impact of Boundary Crossing Rate on Detection Accuracy 23 4.1 Localization System 25 4.2 Results from Real Localization Systems 29 List of Tables 4.1 Scenario Representation of Mobility 27 4.2 CC2420 Radio and ADXL202JE Accelerometer Power Consumption 29 | |
| dc.language.iso | en | |
| dc.subject | 移動狀況 | zh_TW |
| dc.subject | 室內定位 | zh_TW |
| dc.subject | 電源效率 | zh_TW |
| dc.subject | Indoor localization | en |
| dc.subject | Energy efficiency | en |
| dc.subject | Mobility | en |
| dc.title | 適用於邊界偵測之低耗電室內定位系統 | zh_TW |
| dc.title | Energy-Efficient Boundary Detection for RF-Based Indoor Localization Systems | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 96-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 朱浩華(Hao-hua Chu),曾煜棋(Yu-Chee Tseng),金仲達(Chung-Ta King),陳伶志(Ling-Jyh Chen) | |
| dc.subject.keyword | 室內定位,電源效率,移動狀況, | zh_TW |
| dc.subject.keyword | Indoor localization,Energy efficiency,Mobility, | en |
| dc.relation.page | 40 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2008-07-23 | |
| dc.contributor.author-college | 電機資訊學院 | zh_TW |
| dc.contributor.author-dept | 電機工程學研究所 | zh_TW |
| 顯示於系所單位: | 電機工程學系 | |
文件中的檔案:
| 檔案 | 大小 | 格式 | |
|---|---|---|---|
| ntu-97-1.pdf 未授權公開取用 | 693.65 kB | Adobe PDF |
系統中的文件,除了特別指名其著作權條款之外,均受到著作權保護,並且保留所有的權利。
