TY - GEN
T1 - A Hidden Markov Model based dynamic scheduling approach for mobile cloud telemonitoring
AU - Wang, Xiaoliang
AU - Xu, Wenyao
AU - Jin, Zhanpeng
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/4/11
Y1 - 2017/4/11
N2 - 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.
AB - 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.
UR - https://www.scopus.com/pages/publications/85018393004
U2 - 10.1109/BHI.2017.7897258
DO - 10.1109/BHI.2017.7897258
M3 - Conference contribution
AN - SCOPUS:85018393004
T3 - 2017 IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2017
SP - 273
EP - 276
BT - 2017 IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2017
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 4th IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2017
Y2 - 16 February 2017 through 19 February 2017
ER -