Name
Title | ||
|---|---|---|
FairHealth: Long-Term Proportional Fairness-Driven 5G Edge Healthcare in Internet of Medical Things |
Abstract | ||
|---|---|---|
Recently, the Internet of Medical Things (IoMT) could offload healthcare services to 5G edge computing for low latency. However, some existing works assumed altruistic patients will sacrifice quality of service for the global optimum. For priority-aware and deadline-sensitive healthcare, this sufficient and simplified assumption will undermine the engagement enthusiasm, i.e., unfairness. To address this issue, we propose a long-term proportional fairness-driven 5G edge healthcare, i.e., FairHealth. First, we establish a long-term Nash bargaining game to model the service offloading, considering the stochastic demand and dynamic environment. We then design a Lyapunov-based proportional-fairness resource scheduling algorithm, which decouples the long-term fairness problem into single-slot subproblems, realizing a tradeoff between service stability and fairness. Moreover, we propose a block-coordinate descent method to iteratively solve nonconvex fair subproblems. Simulation results show that our scheme can improve 74.44% of the fairness index (i.e., Nash product), compared with the classic global time-optimal scheme. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1109/TII.2022.3183000 | IEEE Transactions on Industrial Informatics |
Keywords | DocType | Volume |
5G,edge healthcare,Internet of Medical Things (IoMT),proportional fairness | Journal | 18 |
Issue | ISSN | Citations |
12 | 1551-3203 | 0 |
PageRank | References | Authors |
0.34 | 0 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xi Lin | 1 | 9 | 1.44 |
| Jun Wu | 2 | 0 | 0.34 |
| Ali Kashif Bashir | 3 | 4 | 2.41 |
| Yang Wu | 4 | 69 | 22.62 |
| Aman Singh | 5 | 0 | 0.34 |
| Ahmad Ali AlZubi | 6 | 0 | 0.34 |