在電力交易市場裡，台電公司會使用各個交易群組回傳之電表監控資料作為即時調度、月度結算的依據。但電表的監控資料卻有著幾個根本的問題。首先，傳輸距離長，但Edge端的網路可靠性不足，造成了明顯的單一脆弱點問題；第二，資料本身缺少完整性、不可否認性的驗證措施，然而這是智慧電表普遍的情形，目前已有研究進行改善；第三，資料模型缺乏一致性的保證，這使得不同端點間對資料筆數及時序關聯認定會有出入。因此本研究便希望探究並解決這幾個問題，並藉由這個研究過程，來深入了解資料一致性的本質，以及如何設計跨地域性的資料傳輸架構。
對此，本研究提出三個機制來解決第一項與第三項問題：第一是藉由建立高可用的Edge端網路以增加傳輸路線，減少Edge端斷線的機率；第二是藉由建立資料間鏈結式關聯，如：時序間的因果關聯，使得Cloud端得以掌握與Edge端資料的數量與次序差異，確保一致性；第三是使用Piggyback的機制進行補值，以利當缺值發生時，可透過自動補值的方式將Cloud端資料補足。最後透過兩項網路面的實驗情境，驗證在這三項機制相互配合下，資料能自動地補足，以達成最終一致性的目標，並使得傳輸中的Edge端DataSender服務失效時，備援的另一組服務就能在短時間內接手並開始回傳資料，以達成高可用性的目標。

Taiwan Power Company (TPC) uses the Electricity Monitoring Data for dispatching ancillary services and the calculating fee of Transaction Groups monthly. However, these data read from AMI on the Edge side have several critical issues. First, the network of the Edge side is not reliable for long-range transmission, because there is a single point of failure problem. Second, the data don’t have self-verification and non-deniable mechanisms for ensuring integrity. Third, there is no guarantee of consistency of the data model, it makes data content and counts will be different between Cloud and Edge sides. This research aims to understand the essentials of consistency and know how to design a good cross-region data transmission architecture by solving these problems.
This thesis proposes three methods to deal with these problems: High-Available Network of Edge, Chained Data Relationship, and Piggyback Fixing. Lastly, the author verifies these suggestions by two Network failure experiments to show how data are automatically fixed and how the standing by DataSender will take control and send to Cloud when another is failed. And how the data in Cloud will become consistent eventually.

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