Abstract
Nowadays, smart environments (e.g., smart home, smart city) are built heavily relying on Cloud computing for the coordination and collaboration among smart objects. The Cloud is typically centralized but smart objects are ubiquitously distributed; thus, data transmission latency (i.e., end-to-end delay or response time) between Cloud and smart objects is a critical issue especially to the applications that have strict delay requirements. To address this concern, a new Fog computing paradigm has been recently proposed by the industry. The key idea is to bring the computing power from the remote Cloud closer to the users, which further enables real-time interaction and location-based services. In particular, the local processing capability of Fog computing significantly scales down the data volume towards the Cloud, and it in turn has great impacts on the entire Internet. In this chapter, smart living as one of the primary elements of smart cities has been conceptualized to EHOPES, namely smart Energy, smart Health, smart Office, smart Protection, smart Entertainment and smart Surroundings. And then the data flow analysis has been investigated to disclose a variety of data flow characteristics. Based on these studies, a data-centered Fog platform has been developed to support smart living. Case studies are also conducted to validate and evaluate the proposed platform.