An Edge-Fog-Cloud computing architecture for IoT and smart metering data

Smart Metering (SM) systems allow frequent and accurate consumption readings that can be the source of multiple applications, generating new business in the future. However, it imposes interesting challenges for Distribution System Operators (DSO), retailers, aggregators and data scientists. The diversity of data formats, structure, granularity, and volume require additional investigation. Thus, this paper emphasizes on an Edge-Fog-Cloud computing architecture and proposes a SM and Internet of Things (IoT) data processing framework to develop applications and extract the meaningful insights from data. This research divides the applications between Edge, Fog and Cloud layers and designs their interactions. Furthermore, this research offers a methodology that distributes the processing between the layers to reduce the communication latency, response time, resource load and utilization. The methodology provides patterns for implementing the algorithms that monitor and control IoT appliances at the Edge layer and perform Load Forecast (LF) and Direct Load Control (DLC) at the Fog layer.