無線感知器網路(Wireless Sensor Networks)包含了大量且低電量的無線感應器(Sensor)裝置，利用這裝置可以提供我們用來觀察生活周遭環境的功用，尤其是過去我們比較無法觀測到的現象。在這一篇論文中，我們考慮怎麼在利用無線感知器網路中有效的利用無線感知器有限電量和儲存空間來回答使用者所提出的區間查詢(range query)的統計量值。我們提出的演算法是基於傳輸量與失真的控制和多層解析度的小波轉換編碼技術來解決在無線感知器上產生的連續資料串流。我們的目標就是要讓系統盡可能的提供使用指在有限定的傳輸量和儲存空間下一個可以得到一個區間查詢的近似統計量值。我們也提出了一個傳輸量與失真度之間控制的最佳解的公式，來決定系統中的無線感應器該如何去控制自己的傳輸量，使得系統的總失真度是最小的。在實驗中，我們驗證了無論是在時間域使用線性回歸和小波壓縮或是在空間域使用關係係數做列順序排列，都可得到很好的壓縮效果來降低傳輸量。最後也驗證了在各種不同的區間查詢，我們整個系統架構在低傳輸量下，使用我們所提出最佳化公式來分配傳輸量，可以有效的將傳輸量分散的分配給不同的無線感知器，使得無線感知器壓縮資料後利用限制的傳輸量可以達到比傳統平均分配傳輸量的失真率還要更低。

Network systems consisting of a large number of small, low-power, wireless sensing devices offer new ability to observe the physical world, especially for monitoring previously unobservable phenomena. In this thesis, we consider answering range queries that request certain of statistics on a subset of nodes in wireless sensor networks in an energy and space efficient way. An algorithm based upon a rate-distortion multi-resolution wavelet coding technique is presented for deliberately selecting coefficients on the continuous sensing data streams. The design goal is to approximate the requested statistics with bits delivered from sensors to the base station as few as possible and with limited space usage. We also deduce a rate-distortion control formula to determine how to optimally allocate bit rate for sensors under constrained total bit rate so as to minimize the overall distortion of the collected data. The experimental results show the R-D proposed method efficiently reduces the transmission amount using the combination of linear regression, spatial correlation and wavelet coding. Finally, we verify our R-D optimal allocation, which can efficiently allocate appropriate bit rate to every sensor node, so as to archive minimizing distortion for range queries.

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