感知網路(CRN)是最近興起的熱門研究領域之一。大部分的連線建立都分別獨立考慮主要使用者(PU)的干擾,降低延遲或最短路徑,鮮少有以最大化平均傳輸總流量為整體考量的研究,為了能在動態環境中最大化平均總流量,本論文提出一個方法透過廣播RREQ和回傳RREP來找出最大效能的路由,當傳輸發生中斷時會迅速重新建立路由來維持最大的平均總流量。並且在不同的感知網路介面中提出OTR和AOTR兩種方法分別找出效能最好的路由和效能近似最好的路由。我們也會證實在DELAY方面AOTR和OTR也會有不錯的表現,尤其是在PU影響的程度很大的時候AOTR的DELAY會很接近最短路徑所挑選出來的方法。模擬結果顯示我們提出的方法流量比其他方法好很多,DELAY方面也有不錯的效果。
Cognitive Radio Networks (CRNs) have recently become one of the most popular research topics. Most routing schemes in this area independently consider the interference level of primary users (PU), the delays or the shortest route. To the best of our knowledge, there are no CRN routing approaches focusing on maximizing the average network throughput. Therefore, this paper proposes a throughput-based distributed routing solution by exchanging RREQ and RREP packets. This method maintains the maximum average network throughput by quickly rebuilding the routing when the flow is interrupted. In addition, we offer two ways in various CRN interfaces, OTR and AOTR. The results from the simulation show that our proposed methods work performs better than existing works.