## 4 DQN-Based Priority/Demanding Resource Management
### DQN-Based Solutions
For future work, we leverage advancing federated learning to minimize the trade-off between communication overhead and joint the cross-protocol with asynchronous. Furthermore, addressing security and privacy concerns will be key focus areas in expanding the effectiveness of our approach. Conceptualization, S.R. and S.K. ([PERSON]); methodology, S.R. and P.T. ; software, P.T. and S.R. ; validation, S.R., I.S. and G.C. formal analysis, I.S. and S.R. ; investigation, S.K. ([PERSON]); resources, S.K. ([PERSON]); data curation, P.T. and S.R. ; writing--original

Figure 7: Average service complete ratios show how efficient the service percentage is over the different time slots. draft preparation, S.R. ; writing--review and editing, S.R., I.S., S.K. ([PERSON]) and P.T. ; visualization, S.R. and G.C. ; supervision, S.K. ([PERSON]); project administration, S.K. ([PERSON]); funding acquisition, S.K. ([PERSON]). All authors have read and agreed to the published version of the manuscript. This work was supported by Institute of Information & Communications Technology Planning and Evaluation (IITP) grant funded by the Korean government (MSIT) (No. RS-2022-00167197, Development of Intelligent 5G/6G Infrastructure Technology for The Smart City); in part by the National Research Foundation of Korea (NRF), Ministry of Education, through the Basic Science Research Program under Grant NRF-2020R1I1A3066543; in part by BK21 FOUR (Fostering Outstanding Universities for Research) under Grant 5199990914048; and in part by the Soonchunhyang University Research Fund. Derived data supporting the findings of this study are available from the corresponding author on request. The authors declare no conflicts of interest. ## References

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