A fog-enabled IoT platform for efficient management and data collection
Pavlos Charalampidis, Ηλίας Τράγος, Alexandros G. Fragkiadakis · 2017
One of the most promising emerging technologies, Internet-of-Things, refers to the interconnection of thousands (or even millions) of smart objects, supporting a large number of applications like environmental monitoring, smart agriculture, e-health, etc. Research groups in both the academia and industry, have proposed and/or developed a significant number of IoT architectures and platforms, however not focusing on platform management-related issues. Furthermore, the vast amount of the sensory data and the rapid proliferation of the smart devices (i.e. sensors) make a new approach regarding efficient data collection and storage inevitable. Fog Computing (FC) is an environment where data are stored and pre-processed before transmitting them to the cloud, having a number of advantages like scalable real-time services, fault detection and isolation, enhanced security and privacy, etc. In this work, we present a fog-enabled IoT platform used for sensory data collection, presenting several metrics that can be used as the basis for a Management-Platform-as-a-Service, able to efficiently monitor the IoT platform and predict potential failures.