A Hidden Markov Model based dynamic scheduling approach for mobile cloud telemonitoring
Xiaoliang Wang, Wenyao Xu, Zhanpeng Jin · 2017
Recent advances in mobile and cloud technologies have been proved to be a promising way to provide healthcare, particularly health monitoring, to individuals in a cost-effective, user-friendly, and pervasive way. However, in practical use, multiple objectives usually need to be considered and fulfilled when deploying such a mobile-cloud-based telemonitoring platform, such as processing latency, energy consumption, and diagnosis accuracy. Given the ever-changing clinical priorities, personal demands, and environmental conditions, it is imperative to explore a smart scheduling and management approach capable of dynamically adjusting the offloading strategy on this mobile-cloud infrastructure. In this study, we propose a new Hidden Markov Model (HMM) based dynamic scheduling approach to allow the system to adapt to the changing requirements.