Mobile Edge Computing Enabled 5G Health Monitoring for Internet of Medical Things: A Decentralized Game Theoretic Approach

The prompt evolution of Internet of Medical Things (IoMT) promotes pervasive in-home health monitoring networks. However, excessive requirements of patients result in insufficient spectrum resources and communication overload. Mobile Edge Computing (MEC) enabled 5G health monitoring is conceived as...

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Published inIEEE journal on selected areas in communications Vol. 39; no. 2; pp. 463 - 478
Main Authors Ning, Zhaolong, Dong, Peiran, Wang, Xiaojie, Hu, Xiping, Guo, Lei, Hu, Bin, Guo, Yi, Qiu, Tie, Kwok, Ricky Y. K.
Format Journal Article
LanguageEnglish
Published New York IEEE 01.02.2021
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
5G mobile communication
Algorithms
Biomedical monitoring
Body area networks
Cloud computing
Edge computing
Energy consumption
Game theory
health monitoring
Internet of Medical Things
Medical services
Mobile communication systems
Mobile computing
Monitoring
Performance evaluation
Sensors
Telemedicine
Upper bounds
Wireless networks
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Abstract The prompt evolution of Internet of Medical Things (IoMT) promotes pervasive in-home health monitoring networks. However, excessive requirements of patients result in insufficient spectrum resources and communication overload. Mobile Edge Computing (MEC) enabled 5G health monitoring is conceived as a favorable paradigm to tackle such an obstacle. In this paper, we construct a cost-efficient in-home health monitoring system for IoMT by dividing it into two sub-networks, i.e., intra-Wireless Body Area Networks (WBANs) and beyond-WBANs. Highlighting the characteristics of IoMT, the cost of patients depends on medical criticality, Age of Information (AoI) and energy consumption. For intra-WBANs, a cooperative game is formulated to allocate the wireless channel resources. While for beyond-WBANs, considering the individual rationality and potential selfishness, a decentralized non-cooperative game is proposed to minimize the system-wide cost in IoMT. We prove that the proposed algorithm can reach a Nash equilibrium. In addition, the upper bound of the algorithm time complexity and the number of patients benefiting from MEC is theoretically derived. Performance evaluations demonstrate the effectiveness of our proposed algorithm with respect to the system-wide cost and the number of patients benefiting from MEC.
AbstractList The prompt evolution of Internet of Medical Things (IoMT) promotes pervasive in-home health monitoring networks. However, excessive requirements of patients result in insufficient spectrum resources and communication overload. Mobile Edge Computing (MEC) enabled 5G health monitoring is conceived as a favorable paradigm to tackle such an obstacle. In this paper, we construct a cost-efficient in-home health monitoring system for IoMT by dividing it into two sub-networks, i.e., intra-Wireless Body Area Networks (WBANs) and beyond-WBANs. Highlighting the characteristics of IoMT, the cost of patients depends on medical criticality, Age of Information (AoI) and energy consumption. For intra-WBANs, a cooperative game is formulated to allocate the wireless channel resources. While for beyond-WBANs, considering the individual rationality and potential selfishness, a decentralized non-cooperative game is proposed to minimize the system-wide cost in IoMT. We prove that the proposed algorithm can reach a Nash equilibrium. In addition, the upper bound of the algorithm time complexity and the number of patients benefiting from MEC is theoretically derived. Performance evaluations demonstrate the effectiveness of our proposed algorithm with respect to the system-wide cost and the number of patients benefiting from MEC.
Author Dong, Peiran
Hu, Xiping
Hu, Bin
Guo, Yi
Guo, Lei
Kwok, Ricky Y. K.
Wang, Xiaojie
Ning, Zhaolong
Qiu, Tie
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  email: ricky.kwok@hku.hk
  organization: Department of Electrical and Electronic Engineering, The University of Hong Kong, Hong Kong
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Snippet The prompt evolution of Internet of Medical Things (IoMT) promotes pervasive in-home health monitoring networks. However, excessive requirements of patients...
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SubjectTerms 5G mobile communication
Algorithms
Biomedical monitoring
Body area networks
Cloud computing
Edge computing
Energy consumption
Game theory
health monitoring
Internet of Medical Things
Medical services
Mobile communication systems
Mobile computing
Monitoring
Performance evaluation
Sensors
Telemedicine
Upper bounds
Wireless networks
Title Mobile Edge Computing Enabled 5G Health Monitoring for Internet of Medical Things: A Decentralized Game Theoretic Approach
URI https://ieeexplore.ieee.org/document/9309177
https://www.proquest.com/docview/2478835867
Volume 39
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