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A fog‐based ubiquitous exercise healthcare monitoring framework for smart cities
Author(s) -
Wu Jiang,
Patrono Luca
Publication year - 2020
Publication title -
internet technology letters
Language(s) - English
Resource type - Journals
ISSN - 2476-1508
DOI - 10.1002/itl2.199
Subject(s) - computer science , cloud computing , smart city , network packet , computer network , internet of things , the internet , real time computing , computer security , world wide web , operating system
Fog‐based exercise healthcare monitoring (EHM) has attracted many interests in the field of smart cities (SCs) as an effective supplement to the cloud‐based applications to reduce the transmission delay and data quantity swarming from smart health devices toward the Internet. However, due to the amount of heterogeneous data from a variety of Internet of Things (IoT) devices, providing fast‐responsive or low‐latency service has always been a great challenge in EHM. Hence, to address these challenges, we propose a fog‐based framework for ubiquitous exercise monitoring capable of efficiently transmitting and processing data at the edge of the network. For this framework, a deep learning‐based traffic prediction method is proposed to ensure optimal network performance. The simulation results demonstrate that our proposed framework has better network performance, in terms of real‐time, average completion time and lost rate of packet queue, compared with several state‐of‐the‐art frameworks.