QoS-Driven Data Processing Algorithms for Smart Electric Grids

Abstract

Smart-grid applications have widely varying data needs as well as bandwidth and latency requirements. The usual approach to accumulating the available data (e.g., from Phasor Measurement Units) at a centralized site and executing all the applications there leads to large network latencies. This article proposes techniques where data packets are prioritized and disseminated based on applications’ data needs and semantics. In particular, these techniques systematically exploit in-network processing capability and filter data in the dissemination network. This filtered data is assigned higher priority compared to the raw unfiltered data—helping meet QoS requirements of various applications. Performance evaluation of our distributed techniques over a testbed designed for the Indian electric grid demonstrates that processing latency for various smart grid applications reduces by at least 50% for large PMU data sizes, compared to the traditional centralized approach.