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研究生:洪偉倫
研究生(外文):Wei-Lun Hung
論文名稱:具省電機制之無線感測網路服務品質控制方法
論文名稱(外文):A Power Saving Design for QoS Control in Wireless Sensor Networks
指導教授:王皓立
指導教授(外文):Hao-Li Wang
學位類別:碩士
校院名稱:國立嘉義大學
系所名稱:資訊工程學系研究所
學門:工程學門
學類:電資工程學類
論文種類:學術論文
畢業學年度:100
語文別:中文
中文關鍵詞:Wireless Sensor NetworksQoS ControlGur GamePower Saving
外文關鍵詞:Wireless Sensor NetworksQoS ControlGur GamePower Saving
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無線感測網路(Wireless Sensor Networks, WSN)是由多個感測器及一個資料匯集端所組成。但在感測器的電量有限的情況下,往往不需要全部的感測器進行感測工作,因此需要以服務品質(Quality of Service, QoS)的控制方式來達到控制運作感測器數量的目的。前人提出以Gur Game演算法來控制感測器數量到指定數目,但此方法並未考量到電量消耗的問題,因此在電力消耗方面存在兩個問題:(1)在感測器數目收斂至目標值前,感測器會經過許多回合頻繁的狀態轉換而消耗掉許多電量。(2)在運作感測器數目收斂至目標值後,只有特定的感測器持續保持運作狀態直到電力耗盡或網路結束,造成電量消耗不均,影響整體網路的生命週期。
因此,為了解決上述的兩個電力消耗問題,本研究在第一部分中提出QC2 (QoS Control with Quick Convergence),藉由設定虛擬總數值的方式,使得運作感測器數量得以快速達到所要求的目標數,減少感測器狀態轉換次數,進而減少在調整過程中所需消耗的電量。而第二部分則是提出具三種省電機制的PSQC (Power Saving Design for QoS Control)。藉由不同電量消耗的狀態、休眠感測器數目最大化和減少狀態轉換的電量消耗三種機制達到省電的目的,進而延長整體網路的生命週期。實驗結果得知,本研究所提出的QC2法可快速收斂至目標值,所需的時間只需要Gur Game法的1/200,有效的減少收斂前狀態轉換所消耗掉的電量。PSQC法則有效的延長了收斂後整體網路的生命週期。

Wireless Sensor Networks (WSNs) consist of lots of sensors for sensing and a sink for collecting data from sensors. The goal of QoS (Quality of service) control is to control the number of active sensors for a desired number. In previous research, the researchers proposed a scheme using Gur Game algorithm for QoS control, but it causes a long convergence time for adjusting the number of active sensor. Moreover, after the long convergence time, the active sensors will not change to other state until run out of energy, which leads to low network lifetime.
For the first problem, we proposed a QoS Control with Quick Convergence method (QC2). QC2 uses virtual total number to calculate an accurate probability for state transition, so the convergence time can be shorter than Gur Game method. For the second problem, we proposed a Power Saving Design for QoS Control method (PSQC). This method uses three power saving designs: subdivide sensor states, reduce the time of high power consumption state transition and increase the number of sensors which are in low power consumption state. The simulation results show that QC2 and PSQC have better performance than the methods proposed in previous researches.

摘要 i
Abstract ii
目錄 iii
圖目錄 vii
表目錄 ix
第1章 簡介 1
1.1 無線感測網路的背景 1
1.2 無線感測網路之服務品質 3
1.3 問題說明與研究目的 4
1.4 論文架構 5
第2章 相關文獻 7
2.1 無線感測網路之服務品質控制 7
2.1.1 Gur Game演算法 7
2.1.2 ACK控制法 8
2.2 減少收斂前電量消耗 9
2.2.1 以調整機率值達到快速收斂 (RCQC) 9
2.2.2 利用虛擬目標改善收斂時間 (VTQC) 10
2.3 減少收斂後的電量消耗 10
2.3.1 Shuffle 11
2.3.2 Gureen Game 11
2.3.3 Energy-Aware QoS Control for Wireless Sensor Network 13
2.3.4 Predictive QoS Control Strategy 14
2.3.5 LARC and LARC-LX 15
2.4 其他相關研究 15
2.4.1 覆蓋導向之無線感測網路 15
2.5 省電相關方法分析 16
第3章 可快速收斂的服務品質控制方法 – QC2 18
3.1 方法概述 18
3.2 判斷網路狀態 19
3.3 狀態轉換機率的計算 19
3.4 狀態鎖定機制 22
3.5 整體運作流程 23
第4章 QC2的模擬實驗 25
4.1 收斂時間比較 25
4.2 QoS達成率比較 26
4.3 總數變化的收斂趨勢 27
4.4 生死環境下的影響 28
第5章 具省電機制的服務品質控制方法 – PSQC 29
5.1 方法架構 29
5.2 細分感測器狀態 30
5.2.1 四個感測器狀態 30
5.2.2 電力模型 31
5.3 減少高耗電的狀態轉換次數 33
5.3.1 加入T2狀態後收斂至目標值的運作 34
5.4 增加休眠感測器 36
5.4.1 增加休眠感測器數量 37
5.4.2 計算休眠時間 39
第6章 PSQC之模擬實驗 41
6.1 實驗概述與參數 41
6.2 細分感測器狀態 42
6.3 減少高耗電狀態轉換機制的效果 42
6.4 增加休眠感測器機制的效果 44
6.5 PSQC V.S. Gureen Game 46
6.5.1 生命週期的比較 46
6.5.2 QoS穩定度比較 48
6.5.3 電量消耗的比較 50
6.6 模擬實驗總結 53
第7章 結論與未來研究 55
7.1 結論 55
7.2 未來展望 56
第8章 參考文獻 58

[1] M. Ayers and Y. Liang, “Gureen Game: An Energy-Efficient QoS Control Scheme for Wireless Sensor Networks” Green Computing Conference and Workshops, 2011

[2] D. M. Blough, and P. Santi, “Investigating Upper Bounds on Network Lifetime Extension for Cell- Based Energy Conservation Techniques in Stationary Ad Hoc Networks,” Mobile Computing and Networking, 2002

[3] J. Chang, and L. Tassiulas, “Routing for maximum system lifetime in wireless ad hoc networks,” Communication, Control and Computing, 1999.

[4] J. Chang, and L. Tassiulas, “Energy conserving routing in wireless ad hoc networks,” International Conference on Computer Communications, 2000.

[5] D. Chen and P. K. Varshney, “QoS Support in Wireless Sensor Networks: A Survey”, International Conference on Wireless Networks, 2004

[6] J. Frolik, “QoS Control for Random Access Wireless Sensor Networks”, IEEE Wireless Communications and Networking Conference, 2004.

[7] W. Heinzelman, A. Chandrakasan, and H. Balakrishnan, “Energy-efficient routing protocols for wireless microsensor networks,” Hawaii International Conference on System Sciences, pp. 1–10, 2000.

[8] Y.-L. Hsu, R.-G. Tsai, H.-L. Wang, ”Virtual Target QoS Control in Wireless Sensor Networks”, National Symposium on Telecommunications, 2010.

[9] Y.-L. Hsu, R.-G. Tsai, and H.-L. Wang,“Rapid Convergence QoS Control in Wireless Sensor Networks,” Taiwan Academic Network Conference, Oct. 2010.

[10] W.-L. Hung, R.-G. Tsai, H.-L. Wang, ”Coverage Based QoS Control in Wireless Sensor Networks”, Mobile Computing Workshop, 2011.

[11] R. Iyer, L. Kleinrock, “QoS Control for Sensor Networks”, IEEE International Conference on Communication, 2003.

[12] J. Kay and J. Frolik, “Quality of service analysis and control for wireless sensor networks”, IEEE International Conference on Mobile Ad-hoc and Sensor Systems, 2004

[13] J. Kay and J. Frolik, “An Expedient Wireless Sensor Automaton With System Scalability and Efficiency Benefits”, IEEE Transactions System, Man and Cybernetics, 2008

[14] B. Liang, J. Frolik, X. Sean Wang, “A Predictive QoS Control Strategy for Wireless Sensor Networks”, Resource Provisioning and Management in Sensor Networks, 2005


[15] B. Liang, J. Frolik, X. Sean Wang, “Energy-Efficient Dynamic Spatial Resolution Control for Wireless Sensor Clusters”, International Journal of Distributed Sensor Networks, 2009

[16] H.-C. Lo, and H.-L. Wang, “Power-saving QoS Control in Wireless Sensor Networks,” Mobile Computing Workshop, Changhua Taiwan, 2007.

[17] S. Singh, M. Woo, and C. Raghavendra, “Power-aware routing in mobile ad hoc networks,” Mobile Computing and Networking, 1998.

[18] A. Sinhua, A. Chandrakasan, "Dynamic Power Management in Wireless Sensor Network", IEEE Design and Test of Computer

[19] R.-G. Tsai, H.-L. Wang, “Shuffle: An Enhanced QoS Control by Balancing Energy Consumption in Wireless Sensor Networks”, Grid and Pervasive Computing, 2010

[20] L. Zhao, C. Xu, Y. Xu, X. Li, ”Energy-Aware QoS Control for Wireless Sensor Network”, Industrial Electronics and Applications, 2006

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