TY - JOUR
T1 - Edge Computing Based Healthcare Systems
T2 - Enabling Decentralized Health Monitoring in Internet of Medical Things
AU - Dong, Peiran
AU - Ning, Zhaolong
AU - Obaidat, Mohammad S.
AU - Jiang, Xin
AU - Guo, Yi
AU - Hu, Xiping
AU - Hu, Bin
AU - Sadoun, Balqies
N1 - Publisher Copyright:
© 1986-2012 IEEE.
PY - 2020/9/1
Y1 - 2020/9/1
N2 - The rapid development of IoMT facilitates pervasive healthcare networks. However, numerous MUs lead to deficient wireless channel and computation resources. Edge computing based healthcare system is appreciated as a satisfactory paradigm to solve this obstacle. Based on the physical bound of WBANs, the IoMT is separated into two sub-networks, that is, intra- WBANs and beyond-WBANs. Considering the characteristics of healthcare systems, the cost of MUs relies on medical urgency, AoI and energy dissipation. In intra-WBANs, the wireless channel resource allocation problem is modeled by a cooperative game. The Nash bargaining solution is utilized to obtain the unique Pareto optimal point. In beyond-WBANs, MUs are considered to be rational and potentially selfish. Thus, a non-cooperative game is formulated to minimize the system-wide cost. To demonstrate the effectiveness of our proposed solution, performance evaluations are conducted with respect to the system-wide cost and the number of MUs benefiting from edge computing. Finally, several research challenges and open issues are discussed for further work.
AB - The rapid development of IoMT facilitates pervasive healthcare networks. However, numerous MUs lead to deficient wireless channel and computation resources. Edge computing based healthcare system is appreciated as a satisfactory paradigm to solve this obstacle. Based on the physical bound of WBANs, the IoMT is separated into two sub-networks, that is, intra- WBANs and beyond-WBANs. Considering the characteristics of healthcare systems, the cost of MUs relies on medical urgency, AoI and energy dissipation. In intra-WBANs, the wireless channel resource allocation problem is modeled by a cooperative game. The Nash bargaining solution is utilized to obtain the unique Pareto optimal point. In beyond-WBANs, MUs are considered to be rational and potentially selfish. Thus, a non-cooperative game is formulated to minimize the system-wide cost. To demonstrate the effectiveness of our proposed solution, performance evaluations are conducted with respect to the system-wide cost and the number of MUs benefiting from edge computing. Finally, several research challenges and open issues are discussed for further work.
UR - http://www.scopus.com/inward/record.url?scp=85084233188&partnerID=8YFLogxK
U2 - 10.1109/MNET.011.1900636
DO - 10.1109/MNET.011.1900636
M3 - Article
AN - SCOPUS:85084233188
SN - 0890-8044
VL - 34
SP - 254
EP - 261
JO - IEEE Network
JF - IEEE Network
IS - 5
M1 - 9083675
ER -