隨著科技的發展，資料儲存的需求也越來越龐大。然而，傳統的儲存媒介已無法跟上這急速成長的需求。在這種情況下，去氧核糖核酸（DNA）儲存被視為一種具有吸引力的替代性儲存媒介。DNA儲存(DNA Storage)具有高密度、長時間存放的耐用性與穩定性，使其成為應對不斷增長的資料需求的理想選擇。然而，DNA資料儲存(DNA Storage)仍面臨著一些挑戰，其中包括高昂的讀寫成本。
幸運的是，DNA計算技術(DNA Computing)的應用為這些挑戰提供了一個可行的解決方案。這種技術允許直接在DNA儲存架構(DNA Storage)中使用資料進行計算，而無需進行昂貴的轉換成傳統二進位制的格式。這種直接計算的方法大大節省了時間和成本，同時提高了計算效率。
基於這些背景，本篇研究的主要目標是提出一個有效率並且具有DNA儲存系統(DNA Storage System)的完整DNA計算機框架，包含開發一種能夠充分利用DNA儲存的優勢並解決其局限性的計算機系統。該系統將集成DNA儲存架構(DNA Storage)和DNA計算單元(DNA Computing Unit)，實現高效的資料儲存和計算功能。
在我們的研究方法中，我們將探索如何最佳化管理DNA儲存架構(DNA Storage)中的資料，包括資料的放置和分類。我們將設計和優化DNA儲存架構的組織方式，以確保資料的快速訪問和高效存取。同時，我們也將研究如何避免DNA資料在運送過程中的污染和錯誤。
為了實現此一目標，我們將結合DNA計算技術和微流體技術(Digital Microfluidics)，以實現對DNA資料的自動處理和計算。這將有助於提高DNA計算機系統的效率和準確性，此解決方案有潛力革新數據儲存和計算領域，且為管理和處理大規模數位資料另闢蹊徑。

With technological advancements, the demand for data storage continues to increase, potentially surpassing the capabilities of traditional storage media in the future. As a result, deoxyribonucleic acid (DNA) storage has emerged as an appealing alternative due to its high density, long-term durability, and stability. DNA storage offers an ideal solution to meet the escalating data demands. However, several challenges persist in DNA storage, notably the high costs associated with reading and writing operations. Fortunately, DNA computing technology presents a possible solution to these challenges. Expensive conversions to traditional binary formats are eliminated by enabling direct computation within DNA storage. This direct computation method offers notable advantages in terms of time and costs savings and enhanced computational efficiency. This paper's primary objective of this research is to propose an efficient and comprehensive DNA computing framework incorporating a DNA storage system. The goal is to develop a computing system that maximizes the benefits of DNA storage while addressing its limitations. Integrating the DNA storage architecture and the DNA computing unit enables efficient data storage and computation. The method to carry out this work is investigating optimal data management strategies within DNA storage, encompassing data placement and classification. We will design and optimize the organizational structure of the DNA storage framework to ensure efficient data access. In addition, we will explore methods to mitigate contamination and errors during DNA data transportation. To achieve these objectives, we will make use of digital microfluidics to automate the processing and computation of DNA data. This framework holds the potential to enhance the efficiency and accuracy of DNA computing systems significantly. Ultimately, this research may offer an alternative avenue for managing and processing large-scale digital data.

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