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研究生:丁之[ㄨ虎]
研究生(外文):Chi-Yi Ding
論文名稱:樹狀式追蹤法於無線感測網路中預測行動收集點之移動路徑
論文名稱(外文):Tree-based Tracking Method to Predict Mobile Sink’s Moving Paths in Wireless Sensor Networks
指導教授:段裘慶段裘慶引用關係
指導教授(外文):Chiu-Ching Tuan
口試委員:連志誠李仁貴
口試委員(外文):Chih-Cheng LienRen-Guey Lee
口試日期:2007-07-02
學位類別:碩士
校院名稱:國立臺北科技大學
系所名稱:電子電腦與通訊產業研發碩士專班
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2007
畢業學年度:95
語文別:中文
論文頁數:93
中文關鍵詞:無線感測網路睡眠機制行動收集點移動路徑樹
外文關鍵詞:wireless sensor networkpower-saving mechanismmobile sinkmoving path tree
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無線感測網路是由諸多小體積、低成本且低電能耗損之裝置,大量佈署所形成之網路系統,感測節點整合了感測器、無線通訊及簡易微處理機系統。使得感測節點佈署於擬偵測的環境中,具有網路易於快速建置之優點。
電能的維護與管理對於感測網路是重要的研究議題,利用節點之睡眠機制,可節省電能消耗,延長總體感測網路的生命週期。本研究主要應用樹狀結構建立一移動路徑樹,用以記錄行動收集點於感測網路中之移動路徑,再依此作分析以預測行動收集點下一步可能移入的區域,如此可預先喚醒該區域內節點而達節能之目的。移動路徑樹除了提供移動路徑的預測之外,同時,也為節點因為高頻率地被喚醒而加速耗能以致失效的情況提供預防的機制,即能事先偵測出可能失效的感測節點。
本移動路徑樹預測法,經由模擬實驗得知,在缺乏足夠的移動路徑記錄時,採用180°作喚醒範圍預測,其區域預測正確率可達80%以上。當移動路徑數逐增後,可將喚醒範圍由180°縮至90°,其區域預測準確率也可達80%以上。移動路徑樹預測比起傳統360°全區域喚醒更節省電能,且預測準確率亦達水準。此外,運用此移動路徑樹,尚可以偵測網路中節點電能消耗情形,如此可預備為即將失效之感測節點,啟用備援路徑以維護感測網路之正常運作。
Wireless sensor network, WSN, consists of many small volume, low cost and low energy sensing devices. The network system is established by deploying a great deal of deployed sensor nodes. The node contains sensor, wireless communication and simple microprocessor. Hence, sensor nodes can be numerously deployed in the desired monitoring environment, and the sensor networks can be constructed quickly and easily.
Energy management is a great research issue for sensor networks. However making nodes into sleeping mode can save the power consumption, and the lifetime of the sensor network could be prolonged. For saving node’s energy, we propose a moving path tree (MPT) to record all moving paths of the mobile sink. By analyzing MPT, the mobile sink can predict the most possible zone where it may move into at the next step. Therefore, only the nodes in the zone require to be waked up, and others still stay in sleep mode for saving energy.
Besides predicting the moving paths, analyzing MPT could judge whether a sensor node will be invalid or not. If the nodes are highly waked to predict the mobile sink’s moving path, they may be failed soon.
The experimental results reveal that if the sink lacks of moving paths recorded to be compared, then create a zone of 180° to predict the next moving path, the accuracy of prediction may reach up to 80%. When the MPT have recorded more moving paths gradually, the prediction range can be shinked from 180° to 90°, and its accuracy of prediction may also reach above 80%. Our MPT prediction may outperform the traditional omni-directional in the accuracy and the degree of saving energy.
Moreover, the analysis of the MPT can detect the residue power energy of nodes and then start the backup paths to keep the network workable when some nodes may be invalid and lead to a hole soon.
中文摘要 I
英文摘要 II
誌謝 IV
目錄 V
表目錄 VII
圖目錄 VIII
第一章 緒 論 1
1-1 研究動機 3
1-2 研究目的 4
1-3 論文架構 4
第二章 文獻探討 5
2-1無線感測網路之資料傳輸協定 5
2-1-1 資料中心協定 5
2-1-2 階層式協定 8
2-1-3 位置導向協定 10
2-2無線感測網路之目標追蹤機制 11
2-2-1 以點為主之追蹤方式 12
2-2-2 以面為主之追蹤方式 17
2-2-3 以節能為考量之追蹤方式 22
2-3 無線感測網路之節能策略 23
2-4 有效率之目標追蹤策略 25
第三章 移動路徑樹架構 27
3-1移動路徑樹之建構 27
3-1-1 移動路徑樹環境設定 27
3-1-2 移動路徑樹建構流程 28
3-1-3 移動路徑樹結構 29
3-2移動路徑樹之建立步驟 32
3-3行動收集點移動預測機制設計 36
3-3-1 收集點移動方向對應 36
3-3-2 收集點移動方向之計數 38
3-3-3 收集點移動修正預測機制 40
3-4移動路徑樹之適用考量 46
3-4-1 感測與通訊半徑考量 46
3-4-2 節能之電能消耗考量 48
第四章 預測效能評估 49
4-1模擬環境建置 49
4-1-1 座標系統 50
4-1-2 隨機路點移動類似模式 51
4-1-3 移動路徑記錄方式 53
4-2評量分析因子 56
4-2-1 區域預測正確率 56
4-2-2 有限區域預測之移動路徑數 57
4-2-3 失效節點偵測門檻值 58
4-3模擬結果分析與比較 58
4-3-1 模擬情境 58
4-3-2 區域預測正確率比較 59
4-3-2-1 一般模式實驗 61
4-3-2-2 特殊模式實驗 64
4-3-2-3 混合模式實驗 67
4-3-3 有限區域預測之移動路徑數比較 69
4-3-3-1 有限區域預測之移動路徑數實驗 70
4-3-3-2 移動路徑數建置成本 72
4-3-4 失效節點偵測門檻值之比較 74
4-3-4-1 SR生存率與mp數目關係實驗 77
4-3-4-2 PAR3(avg)、SR與mp數目關係實驗 80
第五章 結論與未來研究 83
5-1結論 83
5-2未來研究 84
參考文獻 85
附錄
A 專有名詞對照表 88
B 模擬系統簡介 91
C 作者簡歷 93
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