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研究生:李建明
研究生(外文):Jian-Ming Li
論文名稱:在無線感測器網路中以分散式演算法來估算位置
論文名稱(外文):A Distributed Algorithm of Location Estimation for Wireless Sensor Networks
指導教授:許健平許健平引用關係
指導教授(外文):Jang-Ping Sheu
學位類別:碩士
校院名稱:國立中央大學
系所名稱:資訊工程研究所
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2004
畢業學年度:92
語文別:英文
論文頁數:36
中文關鍵詞:無線感測器網路位置估算分散式演算法全球定位系統
外文關鍵詞:Global Positioning SystemDistributed algorithmwireless sensor networklocation estimation
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在無線感測器網路 (Wireless Sensor Networks)中,估算感測器 (sensor nodes)的位置是一個基本且重要的問題。對一個小型的無線感測器網路,感測器可以被規律的設置,因此假設可預先知道所有感測器的位置。然而在一個大型的無線感測器網路中,數量的增加使得對所有感測器的定位變得困難。一個比較合理的解決方法是讓少部分的感測器能夠由全球定位系統 (Global Positioning System)來獲得位置資訊,而其他未掛載GPS 的感測器則是靠著收集附近的資訊來估算出自己的位置。在無線感測器網路中,已經發表了許多集中式的位置估算演算法。在這些演算法中,基地台 (base station)必須去收集所有感測器的資訊並透過複雜的運算後來完成位置估算的工作。為了改進之前的這些研究,我們提出了一個在無線感測器網路中分散式的位置估算演算法。在我們的演算法中,那些原本不知道位置的感測器只需要收集鄰近感測器的位置資訊就可以靠著這些資訊估算出自己的位置。由於我們簡化了估算位置時所需的計算方法,使得我們的演算法可以在簡單的感測器中運作。經過模擬的結果證明使用我們所提出的演算法來估算位置,可以用較少的運算成本來獲得較佳的準確度。
The location estimation of sensor nodes is a fundamental and essential issue for wireless sensor networks (WSNs). In a small scale WSN, the sensor nodes can be placed regularly and the location of each node can be assumed to be known in advance. However, as the number of sensor nodes increases, it is difficult to locate all the sensor nodes in a large scale WSN. A more feasible approach is to assume that only a few sensor nodes get their locations by Global Positioning System (GPS) and the remaining nodes without GPS need to estimate their own locations by gathering the nearby neighboring information. Centralized location estimation algorithms for WSNs have been proposed before. In these algorithms, the base station needs to gather all the location information and estimates the locations of the sensor nodes by applying complicated computations. To improve previous works, we propose a distributed location estimation algorithm for WSNs. In our algorithm, each node without location information only needs to collect the location information of neighboring nodes and estimates its own location according to the collected information. Moreover, we simplified the computation of location estimation, such that it can be computed in simple sensor nodes. The accuracy of the estimation has also been improved. Simulation results show that the proposed algorithm achieves better accuracy of estimative locations with less computation cost.
1 Introduction 1
2 RelatedWorks 4
2.1 Range-based Scheme . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
2.2 Range-free Scheme . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
3 Distributed Location Estimation Algorithm 8
3.1 Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
3.2 Distributed Location Estimation Algorithm . . . . . . . . . . . . . . . . . 11
3.3 The Arithmetic Computations of the DLE Algorithm . . . . . . . . . . . . 12
3.3.1 Calculate Intersection Points of Two Circles . . . . . . . . . . . . . 13
3.3.2 Estimative Rectangle (ER) . . . . . . . . . . . . . . . . . . . . . . 15
3.3.3 Reduce the Size of ER . . . . . . . . . . . . . . . . . . . . . . . . 18
4 Simulations Results 23
4.1 Impact of the Ratio of Beacon Nodes . . . . . . . . . . . . . . . . . . . . . 24
4.2 Impact of the Density of Sensor Nodes . . . . . . . . . . . . . . . . . . . . 28
4.3 Response Rate . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
5 Conclusions and Future Works 30
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