Privacy-Aware Energy Management in the Smart Community using Edge and Cloud Computing Infrastructure

A new architecture for urban sensing in the smart environment is required to facilitate userdefined QoS requirements and, importantly, address the security issues that are present with a cloud-centric approach. The complex topology of IoT networks further exacerbates this problem, as heterogeneous devices must work together utilising a combination of technologies to communicate and process data streams in near real-time. By orchestrating the analysis across the
Edge and Cloud, we can reduce latency and introduce systems to adapt to critical QoS constraints. In particular, a mechanism for privacy preservation can be implemented at the Edge to address the security issues of streaming data to the Cloud. A secure platform for DRM systems in the smart building domain, specifically for energy monitoring, is a gap in current research. This proposal aims to find practical solutions to the aforementioned concerns, making use of real sensor data collected by the heavily-monitored Urban Sciences Building and the publicly available Urban Observatory datasets. Simulation of the data analysis can be further supplemented by recent tools made available to enable the simulation of emerging IoT and Edge-Cloud environments; IOTSim and iFogSim.