A Data-Centric Storage Approach for Monitoring System of Large-Scale Smart Grid

Abstract

Operating data in smart grid are usually collected by a lot of sensors in Cyber-Physical systems. Monitoring data in large-scale smart grid are massive, real-time and dynamic. All on account of that, traditional centralized storage proposals isn'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 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.