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  • 學位論文

在無線感測網路中分散式可容錯事件區域偵測

Distributed Fault-tolerant Event Region Detection of Wireless Sensor Networks

指導教授 : 杜迪榕

摘要


無線感測網路是由大量具備有限運算及傳輸能力的感測節點所組成,近年來感測節點已經設計成極小型且低成本,因此感測節點被廣泛運用在監測難以接近或惡劣的環境。然而這些感測節點是低成本而且易受環境影響,所以在無線感測網路中很容易存在一些故障的感測節點,故障的節點總是回報不可靠的訊息造成決策中心做出錯誤決策或是送出錯誤警報。本研究提出一種針對無線感測網路的分散式可容錯事件區域偵測演算法來解決錯誤與事件混淆問題,此演算法可以找出故障與無故障的感測節點,並且忽略不正常的訊息來避免錯誤警報。除此之外,每一個事件都可以被偵測出來並藉由遠端的基地台找出事件區域。模擬的結果顯示在均勻分佈下錯誤偵測率高於百分之九十二,誤報率幾乎是零,事件偵測率高於百分之九十九;在隨機分佈且感測節點錯誤率最多為百分之三十的狀況下,錯誤偵測率依然高於百分之九十二,誤報率低於百分之一點二,事件偵測率高於百分之八十八。依據實驗結果證實本研究所提出的演算法有高事件偵測率與低誤報率。

並列摘要


A wireless sensor network (WSN) is composed of a large number of sensors equipped with limited computing and communication capability. In recent years, sensors are designed with tiny size and low-cost. Therefore, sensors can be widely used to monitor harsh environment or inaccessible place to us. However, sensors in a WSN are prone to be faulty due to the low-cost design and environmental influence. Faulty sensor always reports unreliable information and the fusion center may makes a wrong decision or sends out a false alarm. This work provides a distributed fault-tolerant event region detection algorithm for wireless sensor networks to solve the fault-event disambiguation problem. The algorithm can identify faulty and fault-free sensors and ignore the abnormal readings to avoid false alarms. Moreover, every event region can also be detected and identified by the base station. The simulation results demonstrate that the fault detection accuracy (FDA) is greater than 92%; the false alarm rate (FAR) is almost 0%, and the event detection accuracy (EDA) is greater than 99% under uniform distribution. The FDA is greater than 92%; the FAR is less than 1.2% and the EDA is greater than 88% under randomly distribution when sensor fault probability is less than 0.3. Our simulation results reveal that the proposed algorithm has high EDA and low FAR.

參考文獻


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被引用紀錄


洪禎瞰(2017)。「問題本位學習」融入班級科展活動對國小五年級學童的自我導向學習之個案研究-以桃園市某國小為例〔碩士論文,中原大學〕。華藝線上圖書館。https://doi.org/10.6840/cycu201700933

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