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A Data-Centric Storage Approach for Efficient Query of Large-Scale Smart Grid

机译:一种以数据为中心的存储方法,用于大规模智能电网的高效查询

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摘要

Smart Grid is an important application in Internet Of Things (IOT). Monitoring data in large-scale smart grid are massive, real-time and dynamic which collected by a lot of sensors, Intelligent Electronic Devices (IED) and etc.. All on account of that, traditional centralized storage proposals aren't applicable to data storage in large-scale smart grid. Therefore, we propose a data-centric storage approach in support of monitoring system in large-scale smart grid: Hierarchical Extended Storage Mechanism for Massive Dynamic Data (HES). HES stores monitoring data in different area according to data types. It can add storage nodes dynamically by coding method with extended hash function for avoiding data loss of incidents and frequent events. Monitoring data are stored dispersedly in the nodes of the same player by the multi-threshold levels means in HES, which avoids load skew. The simulation results show that HES satisfies the needs of massive dynamic data storage, and achieves load balance and a longer life cycle of monitoring network.
机译:Smart Grid是物联网(物联网)的重要应用程序。在大规模智能电网中监视数据是大量传感器,智能电子设备(IED)等的大规模,实时和动态。所有情况都没有适用于数据的传统集中式存储在大型智能电网中存储。因此,我们提出了一种以大规模智能电网的监测系统为中心的数据为中心的存储方法:用于大规模动态数据(HES)的分层扩展存储机制。 HES根据数据类型存储在不同区域中的监测数据。它可以通过使用扩展散列函数的编码方法来动态添加存储节点,以避免事故数据丢失和频繁事件。通过多阈值水平在同一播放器的节点中分散地存储监测数据,这避免了负载偏斜。仿真结果表明,HES满足了大规模动态数据存储的需求,并实现了监控网络的负载平衡和较长的生命周期。

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