隨著5G和物聯網時代的來臨，資料中心(Data Center)的規模和複雜度將會快速增長。為了更加有效率地管理資料中心，分佈式管理任務組(Distributed Management Task Force, DMTF)制定了Redfish標準，其已被視為下一代資料中心基礎設施管理標準。因其具有RESTful界面，能直接向現代工具鏈顯示訊息，所以，很適合廣泛地被應用於各種資料中心管理工具，以利於執行最佳化資源開發。
Redfish的資料模型可被視為一個關聯性資料模型(Relational Data Model)，因此
，可以將Redfish服務視為一個關聯性資料庫管理系統(Relational Database Management System, RDBMS)。又因為Redfish服務中支援客戶端使用查詢字串來靈活地獲取資料是非常重要的功能，因此，我們將RDBMS中常被使用的「啟發式演算法」(Heuristic Algorithm)應用於Redfish查詢中，用以提升Redfish服務之效率，希望解決系統資源被長期佔據的問題。
最後，我們在 OpenBMC 伺服器上進行了實驗。實驗結果顯示：應用啟發式演算法於Redfish之查詢優化架構，總體提升處理時間平均達50%左右。其中包含減少了Redfish 服務的處理時間和增加其處理效能，也間接減少客戶端下載資料與處理資料等資源消耗。總體來說，這樣的方法將可大幅減少Redfish服務於面對現代化工具鏈的請求負載，同時亦可滿足客戶端請求內容之需求。

With the advent of the era of 5G and the Internet of Things (IoT), the scale and complexity of a Data Center will increase rapidly. In order to manage Data Centers more efficiently, the Distributed Management Task Force (DMTF) developed the Redfish standard, which has been regarded as the next-generation Data Center infrastructure management standard. Because Redfish has the RESTful interface, it can directly expose information to modern toolchains. Therefore, Redfish is suitable for being widely used in various Data Center management tools to facilitate the development of resource optimization.
The data model of Redfish can be regarded as a Relational Data Model is that the Redfish service can be regarded as a relational database management system (RDBMS). Because it is a very important function in Redfish service to flexibly support obtaining data by using a query string from the Client side, we apply a Heuristic Algorithm, commonly used in RDBMS, to the query of Redfish in order to improve the efficiency of Redfish service, hoping to solve the problem of system resources being occupied for a long time.
Finally, we conducted the experiment on an OpenBMC server. The experimental results show that the application of the Heuristic Algorithm to the query optimization framework of Redfish can improve the overall processing time by an average of about 50%. Therein, it includes reducing the processing time and increasing the performance of the Redfish service. Moreover, it indirectly reduces the resource consumption of the Client, including the downloading data and processing data. Overall, such an approach will greatly reduce the Request load of Redfish service facing modern toolchains, while also meets the needs of Client Request content.

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