比例式延遲差異模型因具有可預測性和可控制性的特性，故引起眾多的討論和研究。針對各式各樣不同的條件限制，許多研究結果已提出來實現此一模型，然而這些研究方法均只能運行於某些特定的系統負載或訊務分佈。對於比例式延遲差異模型其可預測性的特性而言，提供一個確實可行的方案使其在各種環境之下都能達成是非常重要的。在此篇論文中，我們提出了一個演算法稱為可行延遲差異參數演算法(FDDP)來達成此一目標，此演算法的核心想法是藉由讓控制參數永遠保持正值的原則下調整原本不可行的目標延遲差異參數(DDP)，使其成為可行。經由模擬結果數據的觀察，FDDP不僅能夠得到一組可行的DDP，同時也是一組相當理想的DDP。為了更進一步提高FDDP的效率，我們分別修改了 Leung’s和Feng’s 式子，從而提出二種新的函數評估式稱為modified Lueng’s operator (ML) 與 modified Feng’s operator (MF)。模擬數據結果證明，相較於Leung’s和Feng’s 式子而言ML和MF確實減少了遞迴次數，這意謂著在效能上後者皆比前者來的理想。

The proportional delay differentiation model attracts much attention because of its “predictable” and “controllable” characteristics. Many researches have been proposed to yield this model under various conditions. However, they can only work under certain system utilization or traffic load distribution. Providing a proper approach to achieve the proportional delay differentiation model under all circumstances is very important for the predictable characteristic. In this thesis, we propose the feasible delay differentiation parameter algorithm (FDDP) to conquer this problem. The main idea is to adjust the infeasible desired delay differentiation parameters (DDP) to the feasible DDPs by letting the control parameters always be positive. Observed from numerical results, FDDP not only obtains the feasible DDPs, but also quite perfect DDPs. Further, for enhancing the efficiency of FDDP, we also propose two new functional evaluation operators, modified Lueng’s operator (ML) and modified Feng’s operator (MF), which are modified from the Leung’s and the Feng’s operators, respectively. Numerical results demonstrate that, compared with Lueng’s and Feng’s operators, ML and MF actually reduce the number of iterations, implying the latter is more efficient than the former.

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