在未來裡物聯網(IoT)將會提供大量異質資訊。 其中 IoT 應用之一為智慧電網,
其功能可由 IoT 實現。 智慧電網是新一代的電網系統,它具有雙向溝通的能力。
該新一代智慧電網的其中一個解決方案是藉由部署先進電表基礎設施(AMI)
,達
到自動和分佈式收集儀表數據。公營公司部署智慧電錶,數據集中器(DCU)和
電錶數據管理系統(MDMS)來構建 AMI 架構。集中器從智慧電錶收集大量的訊息,
並將數據傳輸到 MDMS。儘管越來越多地利用電表傳輸過來的訊息來提高電力網
的效率,但大量的數據可能導致數據擁塞。本文使用 REDD 資料集來模擬真實世
界的即時資料。我們提出的算法可以有效地壓縮電錶數據。我們的貢獻是我們提
供一個分析這個問題的策略,並提出一種壓縮算法來壓縮電錶數據。

In the future, the Internet of Things (IoT) has the potential to provide huge volumes
of data. One of IoT applications is a smart grid and its features could be brought by
IoT. A smart grid is a next generation electrical grid system and it is featured by a bidirectional energy flow. A solution to this novel system is to deploy an advanced metering
infrastructure (AMI), which collects meter data automatically and distributively. Utilities
deploy smart meters, data concentrator units (DCU), and meter data management sys-
tem (MDMS) to construct AMI architecture. Concentrators collect ubiquitous messages
from smart meters and transmit aggregated data to MDMS. Although people can use
uiquitous messages to enhance the efficiency of the electricity grid, a massive amount of
messages could cause data congestion. We use REDD data set to simulate the real world
data. Our proposed algorithm could compress meter data efficiently. Our contributions
are listed as follow: First, many types of researches have the intention to address this kind of problem
on AMI system and we provide a relatively complete survey. Second, we also provide a
strategy to analyze this problem and propose a compression algorithm to compact meter
data.

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