本研究透過藍芽傳輸研究裝置時脈偏移現象的過程中，發現藍芽傳輸產生特殊的延遲，我們將此延遲稱之為雨線現象。我們發現雨線會妨礙時脈偏移的量測，因此進一步針對行動裝置與接收端主機進行多種類型變數實驗，研究各變數與雨線現象的關係。在實驗中，由行動裝置傳送時間戳記給接收端，計算出時脈偏移值並判斷雨線現象是否發生。
本研究依據過去之相關研究，比較接收端作業系統、接收端程式、藍芽晶片、封包間隔等變數，透過實驗收集數據提出判斷雨線現象之方法。透過WiFi長時間測量各行動裝置，以此為基準判別個變數影響時脈偏移程度，各變數實驗以霍氏轉換法篩選主群體在使用線性規劃來估算時脈偏移。透過本研究之方法可明顯區分出雨線現象是否發生。
經由實驗結果分析，雨線現象與接收端主機之作業系統與接收端所使用之程式語言明顯相關，目前我們只能在Microsoft Windows下，Python及C#程式語言觀測到雨線現象。另外，藍芽晶片的種類不會造成影響。最後，雨線現象與發送端發送封包之時間間隔呈現負相關的關係，也就是說發送間隔越長，每條雨線上的點就越少。

In this study, we analyze a specific phenomenon when measuring the transmission delay via Bluetooth communication. We call this phenomenon raining as the delays of consecutive packets fall in lines of the same slope. Since the raining phenomenon might interfere measuring clock skews of remote devices, we conducted experiments on mobile devices with few independent variables to analyze the relationship between these variables and raining lines. In the experiment, the mobile devices send timestamps to the same receiver periodically. We calculate transmission delays to determine whether the raining phenomenon occurs or not.
Based on past studies, we chose operating system, program execution environment of receiver, Bluetooth chip and packet sending interval as candidates for independent variables. We also designed an algorithm, according to the fixed pattern of raining lines, to automatically detect if raining happens. For every mobile device, we measured its clock skew via WiFi and use it as a benchmark to determine the effect of different variables. These experiments use Hough transform to pick representative data and use linear programming method to estimate clock skew.
Our experiment results show that raining has high correlation with operating systems and program execution environments of the receiver. Raining lines only happen in Microsoft Windows operating system and programming languages like Python and C#. However, Bluetooth chips of different models do not affect the raining lines. Finally, the results show negative correlation between raining lines and the sending intervals: the bigger the interval be, the less number of points each raining line has.

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