Energy-Aware Edge-Cloud Computation Offloading for Smart Connected Health

Smart connected healthcare is an emerging technology in the context of smart cities. The connected network aims to provide efficient and effective remote patient care. In such scenarios, edge and clouds come into the picture to offload computation from sensors and mobile devices, monitoring patient's health conditions, having limited processing capabilities to the edge and/or the cloud. The problem of optimizing the energy consumption of the edge and cloud servers in this offloading scenario is crucial. However, existing research efforts focus on sensors or cloud energy optimization. They do not consider the edge and cloud as part of the offloading strategy. In this paper, we address this void by proposing a novel energy-aware offloading algorithm for smart connected healthcare, which optimizes the energy of the edge-cloud computing platform for compute-intensive applications. The experimental results show that our proposed algorithm is a promising approach to energy savings.