隨著無線通訊技術的發展，使得行動用戶可以透過無線的方式連結網際網路，接受最新的訊息。然而各種多元化的服務都需要有高速的傳輸來達成，因此無線網路頻寬的提升更顯重要。然而慾望及需求無限，但頻寬終究有限，永遠難以滿足人類的需求，因此使用資料預取策略來減少行動用戶端的等待時間已成為單純提升網路頻寬之外的重要方法之一。
在行動通訊系統中，當使用者提出與位置相依的資料請求時，爲了減少直接由無線網路伺服器下載資料的等待時間，行動用戶端可以使用預取的資料直接回覆給使用者，然而既有之預取策略只考量提升快取命中率，卻忽視預取所帶來的其頻寬成本增加。因此本論文提出''模糊式調變資料預取''。其能夠依照行動用戶端的移動慣性(向前移動機率)及網路狀態(網路流量負載)動態地調整預取資料量，藉以較小的頻寬成本來縮短用戶端之存取延遲，而達到較佳的預取效能。
由模擬實驗來比較模糊式調變資料預取、距離式資料預取、路徑式資料預取及調變式資料預取等策略的效能差異。並以平均存取延遲、平均存取成本及預取效能作為評量因子來分析這四種策略，經由實驗結果證實模糊式調變資料預取策略之平均存取成本及預取效能的確優於其它三者，更能有效地利用資料預取策略提升行動網路的服務品質。

With the developments of wireless communications, users surf on the internet by wireless links, and they get the newest information. However, various kinds of service need high-speed transmission media to match the requirements, therefore it is more and more important to enhance the bandwidth of wireless networks. It’s very difficult to satisfy mankind's demands, since desires and demands are limitless, nevertheless, bandwidth is limited. Consequently the prefetch strategies is adopted to reduce user’s waiting time.
In the mobile communication systems, uses request for the location dependent data, and mobile stations reply to users by the prefetched data directly. However, the existing strategies merely improved the hit ratio without taking the bandwidth cost of prefetch into account. For this reason, we propose "Fuzzy-based Adaptive Data Prefetch". It can adjust the prefetch data size dynamically according to user's movement inertia (probabilities of moving forward) and network states (the traffic load of networks), and it reduce the access delay with lower bandwidth cost, and higher prefetch efficiency.
We can find the differences of "Fuzzy-based Adaptive Data Prefetch", "Distance-based Data Prefetch", "Path-based Data Prefetch" and "Adaptive Data Prefetch" by simulations. We analysis the four strategies with four matrices : mean access delay、mean access cost、mean access efficiency, and it’s proved via the experimental results that the mean access cost and mean access efficiency of "Fuzzy-based Adaptive Data Prefetch" is really superior to others, and it can utilize the prefetch strategy to improve the QoS of Mobile Networks.

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