在不穩定無線感測網路下之資料收集路徑演算法

Abstract

現今社會中智慧裝置越來越多，這些裝置大多有無線網路連結，並執行著資料收集與特定內容播放。針對這些節點的相互聯結，控制以及操作，我們稱為物聯網相關技術。其中，內容的收集以及共用，在物聯網中是一個相當重要的議題。另一方面，壓縮感知的技術讓收集分散的資料變得更加有效率，並可以大幅減少資料量傳輸。在這篇論文中，我們使用提出一個路徑規劃的方法，結合壓縮感知演算法，以有效率的收集各地必要的資料。此方法在空間中存在有一些受訊號干擾而不能傳輸的區域時，還是能傳輸資料，不受太大的影響。且當訊號干擾不存在時，傳輸的速率規模維持不變，皆為θ(NW/M) 。我們也架構出網路資料傳輸速率的模型，並進行相關模擬，證實了我們的演算法的確具有較好的傳輸效率。

Nowadays, more and more smart device appears in our society. Most of them connect to Internet. They collect data via Internet and play specific content. The technology of connecting, controlling and operating device, we call it Internet of Thing (IoT) technology. In this domain, how to collect and share content is a very important issue. On the other hand, Compressive Sensing (CS) provides a new method to collecting data more efficiently, and it largely decreases the data traffic. We propose a routing algorithm for single-sink data collection, which combine with CS, to collect needed file data efficiently, which the capacity is θ(NW/M). Our method can still work when there is some area can’t transmit data because of signal interference without losing too many data. We also construct the model to calculate data transmission speed, and make the simulation. It proves that our algorithm has the better transmission efficiency indeed.