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作者(中文):陳騰翔
作者(外文):Chen, Teng-Xiang
論文名稱(中文):在不可靠的無線感測網路利用資料匯集以及可調整的傳輸範圍機制建立最大生命週期資料收集樹
論文名稱(外文):Constructing Maximum-lifetime Data Gathering Tree in Unreliable Wireless Sensor Networks with Data Aggregation and Adjustable Transmission Ranges
指導教授(中文):林華君
口試委員(中文):蔡榮宗
陳俊良
學位類別:碩士
校院名稱:國立清華大學
系所名稱:資訊工程學系
學號:101062650
出版年(民國):103
畢業學年度:102
語文別:中文
論文頁數:51
中文關鍵詞:無線網路資料收集樹生命週期
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在真實世界的感測網路中,為了維護可靠度,常常會使用Acknowledgement的機制,造成sensor額外的能量消耗,也使得傳輸行為變得複雜;在本篇論文中,網路環境為使用tree-based topology,進行資料的收集並傳回root,即base station,所有sensor都採用可調整且能互不相同的傳輸能量等級,傳送ACK亦須要選擇使用不同傳輸能量等級。本篇論文希望在此環境下,探討建立最大生命週期的data gathering tree。
第一章、 Introduction 1
第二章、 802.15.4 Protocol Analysis And The Derivation of Error Performance 4
A. IEEE 802.15.4 Protocol 4
B. DerivationData Frame and ACK Frame Error Rate 9
C. Derivation Data Frame and ACK Frame transmitting expectation 11
第三章、 Sensor Network Model 15
第四章、 Maximum Lifetime Tree Problem 22
第五章、 Lower bound on the normalized load 24
第六章、 Proposed Algorithm 31
A. Partial Bound on the normalized load of the optimal data gathering tree problem 32
B. Definition of Improvement 36
C. Classification of nodes 37
D. Verification of principle 38
E. Detail of proposed algorithm 40
第七章、 Simulation 43
A. Simulation Model 43
B. Results for unreliable wireless sensor network 46
第八章、 Conclusion 50
第九章、 Reference 51
[1] J. R. Barry, E. A. Lee, D. G. Messerschmitt, “Digital Communication,”3th ed.
[2] S. Madden, R. Szewczyk, M. J. Franklin, and D. Culler, “SupportingAggregate Queries Over Ad-Hoc Wireless Sensor Networks,” In Proceedings of 4th IEEE Workshop on Mobile Computing and SystemsApplications, pp. 49-58, June 2002.
[3] K. Kalpakis, K. Dasgupta, and P. Namjoshi, “Efficient algorithms formaximum lifetime data gathering and aggregation in wireless sensornetworks,” Computer Networks, Vol. 42, no. 6, pp. 697-716, Aug. 2003.
[4] Y. Xue, Y. Cui, and K. Nahrstedt, “Maximizing lifetime for data aggregationin wireless sensor networks,” Mobile Networks and Applications,vol. 10, no. 6, pp. 853-864, Dec. 2005.
[5] J. Stanford and S. Tongngam, “Approximation algorithm for maximumlifetime in wireless sensor networks with data aggregation,” in Pro-ceedings of the Seventh ACIS International Conference on Software En-gineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing (SNPD), pp. 273-277, June 2006.
[6] K. Kalpakis and S. Tang, “A combinatorial algorithm for the MaximumLifetime Data Gathering and Aggregation problem in sensor networks,”in Proceedings of the International Symposium on a World of Wireless,Mobile and Multimedia Networks (WoWMoM), pp. 1-8, June 2008.
[7] H. ¨O. Tan and ˙I. K¨orpeoˇglu, “Power Efficient Data Gathering andAggregation in Wireless Sensor Networks,” ACM SIGMOD Record, vol. 32, no. 4, pp. 66-71, Dec. 2003.
[8] W. Liang and Y. Liu, “Online Data Gathering for Maximizing Network Lifetime in Sensor Networks,” IEEE Transaction on Mobile Computing,vol. 1, no. 2, pp. 2-11, Jan. 2007.
[9] Y. Wu, Z. Mao, S. Fahmy, and N. B. Shroff, “Constructing Maximum-Lifetime Data-Gathering Forests in Sensor Networks,” IEEE Transactionon Networking, vol. 18, no. 5, pp. 1571-1584, Oct. 2010.
[10] H. C. Lin, F. J. Li, and K. Y. Wang, “Constructing maximum-lifetime data gathering trees in sensor networks with data aggregation,” inProceedings of the IEEE ICC, May 2010.
[11] IEEE standard for information technology – telecommunications and information exchange between systems - local and metropolitan area networks specific requirements part 15.4: wireless medium access control (MAC) and physical layer (PHY) specifications for low-rate wirelesspersonal area networks (LR-WPANs),” IEEE Std 802.15.4-2003.
[12] P. Gupta, and S. G. Wilson, “IEEE 802.15.4 PHY Analysis:Power Spectrum and Error Performance,”India Conference, 2008. INDICON 2008. Annual IEEE, vol.1, pp.171-176, Dec. 2008.
[13] L. Shi and A. Fapojuwo, “Tdma scheduling with optimized energy efficiency and minimum delay in clustered wireless sensor networks,” Mobile Computing, IEEE Transactions on, vol. 9, no. 7, pp. 927 –940, July 2010.
[14] T. Rappaport, K. Blankenship, and H. Xu, “Propagation and radio system design issues in mobile radio systems for the GloMo project,” VirginiaPolytechnic Institute and State University, Jan 1997.
[15] S. Rao, “Estimating the ZigBee transmission-range ISM band,” EDN,vol. 52, no. 11, pp. 67–74, 2007.
[16] S. Y. Seidel and T. S. Rappaport, “914 MHz path loss prediction models for indoor wireless communications in multifloored buildings,” IEEE Trans. Antenna and Propagation, vol. 40 Issue: 2, pp. 207-217, Feb. 1992.
[17] L. Couch, Digital and Analog Communication Systems. NewYork:Macmillan, 1993.
[18] Texas Instruments, “A True System-on-Chip Solution for 2.4-GHz IEEE 802.15.4 and ZigBee Applications,” [Online]. Available:http://www.ti.com/lit/ds/symlink/cc2530.pdf
[19] Y. Shen, Y. Li, Y. H. Zhu, “Constructing Data Gathering Tree to Maximize Lifetime of Unreliable Wireless Sensor Network under Delay Constraint,” in Wireless Communications and Mobile Computing Conference (IWCMC),no. 8, pp. 100-105, Aug, 2012.
[20] Y. Li, Y. Y. Shen, K. K. Chi, “A Lifetime-Preserving and Delay-Constrained Data Gathering Tree for Unreliable Sensor Networks,” in KSII Transactions on Internet and Information Systems, March 2012
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