隨著多媒體應用程式的發展以及使用者客製化的需求，使得目前網際網路所採用的盡力服務(Best Effort)已不能滿足這些多變化的需求。所以IETF(Internet Engineering Task Force)就提出了將服務分級之差異式服務網路(differentiated service network, DiffServ)架構來提供不同的服務品質等級的網路服務。
在差異式服務網路當中，核心伺服器(core router)使用隨機早期偵測(Random Early Detection, RED)演算法，此演算法的缺點在於當網路發生壅塞時會以隨機挑選並丟棄網路上封包來維持流量穩定，如此一來會使得路由器的佇列長度變化太大而造成不可預期的佇列延遲。本論文設計了一個在差異式服務網路架構下，以費雪線性區別(Fisher Linear Discriminate, FLD)為基礎，具有壅塞相依的封包丟棄器。使用FLD計算封包丟棄機率除了可以減少運算時間外，還可以避免在RED演算法中隨機挑選丟棄封包的缺點。除此之外，在挑選FLD函數時所需的樣本數上，本論文所提出的壅塞相依的取樣方法會針對實際網路流量的壅塞程度來決定應取樣的樣本間隔及大小，然後挑選出適當的封包數來建立封包丟棄器。
本論文使用NS2模擬軟體來模擬一個具有動態流量變化及壅塞的網路環境，並與其他著名的主動式佇列管理(Active Queue Management, AQM)方法如RED比較，模擬的結果針對各類別的服務速率、佇列變化、點對點之間的延遲、延遲誤差及傳輸率都有良好的成效和顯著的改善，而壅塞敏感性的取樣方法在偵測實際網路流量上也有顯著的效果。

The internet is being used by business and user communities with diversified quality of service expectations (QoS), leading to applications with different QoS levels requirements. The Internet Engineering Task Force (IETF) has proposed differentiated service (DiffServ) to provide class-based QoS in IP-based networks for traffic management.
In a DiffServ network, the core routers use the Random Early Detection (RED) algorithm, which performs random packet dropping schemes when congestion occurs. Since RED follows the probability dropping mechanism, it cannot stabilize the queue length variation, and therefore leads to unpredictable end-to-end delay and jitter. This thesis designs a packet dropping mechanism with a congestion-sensitive sampling method for DiffServ based on the Fisher Linear Discriminate (FLD) approach. Using FLD can abbreviate the calculation of the packet dropping probability and generate the random number which is necessary for all RED schemes. In addition, the congestion-sensitive sampling method obtains a good approximation of the network flow distribution, and then devotes the appropriate number of samples for generating FLD functions.
This thesis uses simulation software to simulate a congested DiffServ network with flow dynamics and compares it with some popular AQM methods, such as RED and the priority queue scheme. The simulation result shows good performance and significant improvement in the field of stable service, queue length, one way delay, jitters, goodput and packet loss rate. The congestion-sensitive sampling method also has a good result in predicting the actual network situation.

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