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

Abstract

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.