ICCF: An Information-Centric Collaborative Fog Platform for Building Energy Management Systems

Abstract

In order to construct future large-scale Internet of Things (IoT) networks, Fog computing is a promising paradigm that brings big data processing capability, storage, and control from a remote cloud closer to the end users/things. However, the majority of prior studies have focused on the data connection to realize a vertical Cloud-Fog-devices' continuum. In this paper, we propose an information-centric collaborative Fog (ICCF) platform, empowered by a novel horizontal Fog-to-Fog layer. Specifically, the ICCF enhances sensor data processing performance by enabling horizontal data transfer in the Fog layer through connectionless name-based Fog-to-Fog data transmission. It utilizes the Fog node's distributed data processing power to achieve a satisfactory data processing performance, while communication with the Cloud is only required to report detected anomalies. Moreover, because the connectionless name-based scheme significantly reduces data connection overhead, this guarantees real-time communication and the ability of processing large-scale IoT data. Building energy management system (BEMS) for detecting abnormal sensor data is adopted as a case study to illustrate our design philosophy and, more importantly, to validate the advantages of the proposed ICCF by conducting a variety of experiments based on the sensor data collected from a real-world indoor environment.

Keywords

• Building energy management system
• fog computing
• information-centric networking
• Internet of Things
• machine learning
• sensor data processing