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以GeoJSON壓縮技術增進網路資料傳輸效能之研究 / Efficiency improvement of spatial data transmission by GeoJSON compression techniques陳欣瑜, Chen,Hsin Yu Unknown Date (has links)
標準化的地理資料交換格式是開放式地理資訊系統不可或缺的一環,可提供不同的平台經由統一的交換格式而順利進行資料交換。GeoJSON除了具備基本的資料互通性外,其結構簡單且容易讀取的特性為地理資訊服務軟體帶來許多效益。然而座標資料量之多寡直接影響資料傳輸效能,為提昇傳輸效率,必須配合有效的資料壓縮技術以降低傳輸之資料量。此外,GeoJSON壓縮方法的設計與結構訴求,也須融合GeoJSON的概念,以簡單、方便運用與容易了解為目標。
本研究提出一套GeoJSON壓縮技術進行空間資料的壓縮,以降低資料量而增進Web GIS地理資料傳輸的效能。除評估其壓縮效率,並透過不同規模以及不同型態的地理資料,分析影響壓縮效率的原因。最後藉由HTTP壓縮技術輔助,並從資料傳遞的時間與壓縮率,評估本研究提出的方法所帶來的成效。我們同時以單向雜湊函數,建立資料傳遞時的檢查機制,以確保資料傳遞時的正確性與一致性。
實作中,我們採用GeoJSON壓縮技術,進行座標資料的大小減量實驗,結果顯示本研究方法可以得到不錯的壓縮成果與傳輸效能,並且可避免資料傳輸發生問題。 / Standardized GIS data exchanging format is an essential part of Open GIS. This enables GIS data providers, software developers, and system integrators to exchange GIS data from different platform. The simple structure of GeoJSON not only has the data interoperability potential but also has the characteristics of easy processed and readability. These properties directly benefit the GIS service software. However, the amount of spatial information encoded in GIS documents usually has direct impact to the efficiency of GIS data transmission. In order to improve the data transmission efficiency, one has to reduce the amount of spatial data transmitted through data compression techniques.
In this thesis, we proposed a data compression mechanism for spatial data. Our mechanism, co-operated with the concept of GeoJSON, aim at simple, easy to understand, and easy to use, can reduce the amount of spatial data transmitted and improve the transmission efficiency. We analyzed the compression ratio of various data types and data amounts through different base parameters. We also measured the system response time reduced using this method and compared with the combination of using our method as well as the HTTP compression modules. A one-way hashing technique is used to ensure data accuracy and consistency during the transmission processes. The experimental results show that our GeoJSON-based compression mechanism can significantly reduce the file size of spatial data and improve the efficiency of spatial data transmission. In addition, the data communication errors can be avoided.
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