4 Conclusion
The priority-based mobile edge computing task migration model greatly improves the
processing efficiency and quality of emergency tasks. Compared with the general
migration model without task priority, it has great advantages and can be applied in
many fields and industries such as telemedicine. At the same time, there are still some
areas to be improved, such as bringing the energy model of ordinary tasks into consideration, setting the capacity of MEC servers to a limited situation, considering the
mobility management of mobile device, and so on.
Acknowledgements. This work is jointly supported by the National Natural Science Foundation of China (No. 61601082, No. 61471100, No. 61701503, No. 61750110527).
References
1. Bourne PE, Lee KC, Ma JD et al (2011) Telemedicine, genomics and personalized medicine:
synergies and challenges. Curr Pharmacogen Pers Med (Former Curr Pharmacogen) 9(1)
2. Chen X, Jiao L, Li W et al (2015) Efficient multi-user computation offloading for mobileedge cloud computing. IEEE/ACM Trans Netw 24(5):2795–2808
3. Jiang F, Zhang X, Peng J et al (2018) An energy-aware task offloading mechanism in
multiuser mobile-edge cloud computing. Mob Inf Syst 2018(4):1–12
4. Kamoun F (2008) Performance analysis of a non-preemptive priority queuing system
subjected to a correlated Markovian interruption process. Comput Oper Res 35(12):3969–
3988
5. Liu CF, Bennis M, Poor HV (2017) Latency and reliability-aware task offloading and
resource allocation for mobile edge computing
6. Mach P, Becvar Z (2017) Mobile edge computing: a survey on architecture and computation
offloading. IEEE Commun Surv Tutor 99:1-1
7. Seung-Woo K, Kaifeng H, Kaibin H (2018) Wireless networks for mobile edge computing:
spatial modeling and latency analysis. IEEE Trans Wirel Commun 1-1
8. Wootton R (1997) Telemedicine: the current state of the art. Minim Invasive Ther Allied
Technol 6(5–6):393–403
9. Zhang J, Hu X, Ning Z et al (2017) Energy-latency trade-off for energy-aware offloading in
mobile edge computing networks. IEEE Internet Things J 1-1
10. Zhang K, Leng S, He Y et al (2018) Mobile edge computing and networking for green and
low-latency internet of things. IEEE Commun Mag 56(5):39–45
Research on Multi-priority Task Scheduling Algorithms …
147
The priority-based mobile edge computing task migration model greatly improves the
processing efficiency and quality of emergency tasks. Compared with the general
migration model without task priority, it has great advantages and can be applied in
many fields and industries such as telemedicine. At the same time, there are still some
areas to be improved, such as bringing the energy model of ordinary tasks into consideration, setting the capacity of MEC servers to a limited situation, considering the
mobility management of mobile device, and so on.
Acknowledgements. This work is jointly supported by the National Natural Science Foundation of China (No. 61601082, No. 61471100, No. 61701503, No. 61750110527).
References
1. Bourne PE, Lee KC, Ma JD et al (2011) Telemedicine, genomics and personalized medicine:
synergies and challenges. Curr Pharmacogen Pers Med (Former Curr Pharmacogen) 9(1)
2. Chen X, Jiao L, Li W et al (2015) Efficient multi-user computation offloading for mobileedge cloud computing. IEEE/ACM Trans Netw 24(5):2795–2808
3. Jiang F, Zhang X, Peng J et al (2018) An energy-aware task offloading mechanism in
multiuser mobile-edge cloud computing. Mob Inf Syst 2018(4):1–12
4. Kamoun F (2008) Performance analysis of a non-preemptive priority queuing system
subjected to a correlated Markovian interruption process. Comput Oper Res 35(12):3969–
3988
5. Liu CF, Bennis M, Poor HV (2017) Latency and reliability-aware task offloading and
resource allocation for mobile edge computing
6. Mach P, Becvar Z (2017) Mobile edge computing: a survey on architecture and computation
offloading. IEEE Commun Surv Tutor 99:1-1
7. Seung-Woo K, Kaifeng H, Kaibin H (2018) Wireless networks for mobile edge computing:
spatial modeling and latency analysis. IEEE Trans Wirel Commun 1-1
8. Wootton R (1997) Telemedicine: the current state of the art. Minim Invasive Ther Allied
Technol 6(5–6):393–403
9. Zhang J, Hu X, Ning Z et al (2017) Energy-latency trade-off for energy-aware offloading in
mobile edge computing networks. IEEE Internet Things J 1-1
10. Zhang K, Leng S, He Y et al (2018) Mobile edge computing and networking for green and
low-latency internet of things. IEEE Commun Mag 56(5):39–45
Research on Multi-priority Task Scheduling Algorithms …
147