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Fan, and J. Ren, \u201cData age aware scheduling for wireless powered mobile-edge computing in industrial internet of things,\u201d IEEE Transactions on Industrial Informatics, vol.17, no.1, pp.398-408, 2020. 10.1109\/tii.2020.2985723","DOI":"10.1109\/TII.2020.2985723"},{"key":"5","doi-asserted-by":"publisher","unstructured":"[5] L. Wu, Y. Xiong, K.-Z. Liu, and J. She, \u201cA real-time pricing mechanism considering data freshness based on non-cooperative game in crowdsensing,\u201d Information Sciences, vol.608, pp.392-409, 2022. 10.1016\/j.ins.2022.06.068","DOI":"10.1016\/j.ins.2022.06.068"},{"key":"6","doi-asserted-by":"crossref","unstructured":"[6] Q. Kuang, J. Gong, X. Chen, and X. Ma, \u201cAge-of-information for computation-intensive messages in mobile edge computing,\u201d 2019 11th International Conference on Wireless Communications and Signal Processing (WCSP), IEEE, pp.1-6, 2019. 10.1109\/wcsp.2019.8927944","DOI":"10.1109\/WCSP.2019.8927944"},{"key":"7","doi-asserted-by":"publisher","unstructured":"[7] Q. Kuang, J. Gong, X. Chen, and X. Ma, \u201cAnalysis on computation-intensive status update in mobile edge computing,\u201d IEEE Transactions on Vehicular Technology, vol.69, no.4, pp.4353-4366, 2020. 10.1109\/tvt.2020.2974816","DOI":"10.1109\/TVT.2020.2974816"},{"key":"8","doi-asserted-by":"publisher","unstructured":"[8] L. Liu, X. Qin, Z. Zhang, and P. Zhang, \u201cJoint task offloading and resource allocation for obtaining fresh status updates in multi-device mec systems,\u201d IEEE Access, vol.8, pp.38248-38261, 2020. 10.1109\/access.2020.2976048","DOI":"10.1109\/ACCESS.2020.2976048"},{"key":"9","doi-asserted-by":"publisher","unstructured":"[9] A. Muhammad, I. Sorkhoh, M. Samir, D. Ebrahimi, and C. Assi, \u201cMinimizing age of information in multiaccess-edge-computing-assisted iot networks,\u201d IEEE Internet of Things Journal, vol.9, no.15, pp.13052-13066, 2021. 10.1109\/jiot.2021.3139044","DOI":"10.1109\/JIOT.2021.3139044"},{"key":"10","doi-asserted-by":"publisher","unstructured":"[10] Z. Qin, Z. Wei, Y. Qu, F. Zhou, H. Wang, D.W.K. Ng, and C.-B. Chae, \u201cAoi-aware scheduling for air-ground collaborative mobile edge computing,\u201d IEEE Transactions on Wireless Communications, vol.22, no.5, pp.2989-3005, 2023. 10.1109\/twc.2022.3215795","DOI":"10.1109\/TWC.2022.3215795"},{"key":"11","doi-asserted-by":"publisher","unstructured":"[11] G. Zhang, C. Shen, Q. Shi, B. Ai, and Z. Zhong, \u201cAoi minimization for wsn data collection with periodic updating scheme,\u201d IEEE Transactions on Wireless Communications, vol.22, no.1, pp.32-46, 2023. 10.1109\/twc.2022.3190986","DOI":"10.1109\/TWC.2022.3190986"},{"key":"12","doi-asserted-by":"publisher","unstructured":"[12] W.Y.B. Lim, Z. Xiong, J. Kang, D. Niyato, C. Leung, C. Miao, and X. Shen, \u201cWhen information freshness meets service latency in federated learning: A task-aware incentive scheme for smart industries,\u201d IEEE Transactions on Industrial Informatics, vol.18, no.1, pp.457-466, 2022. 10.1109\/tii.2020.3046028","DOI":"10.1109\/TII.2020.3046028"},{"key":"13","doi-asserted-by":"crossref","unstructured":"[13] Y. Yang, W. Wang, R. Xu, G. Srivastava, M. Alazab, T.R. Gadekallu, and C. 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Abedin, \u201cIncentive mechanism for competitive edge caching in 5G-enabled Internet of things,\u201d Computer Networks, vol.213, p.109096, 2022. 10.1016\/j.comnet.2022.109096","DOI":"10.1016\/j.comnet.2022.109096"},{"key":"30","doi-asserted-by":"crossref","unstructured":"[30] H. Zhang, D. Liu, X. Liu, R. Wang, L. Sun, F. Zhang, F. Zhao, S. Xu, and W. Zhang, \u201cIncentives for Clustered Federated Learning in 5G Networks: Considering Data Heterogeneity.\u201d 2024 Sixth International Conference on Next Generation Data-driven Networks (NGDN), IEEE, pp.263-267, 2024. 10.1109\/ngdn61651.2024.10744170","DOI":"10.1109\/NGDN61651.2024.10744170"},{"key":"31","doi-asserted-by":"publisher","unstructured":"[31] M. Liu and Y. Liu, \u201cPrice-based distributed offloading for mobile-edge computing with computation capacity constraints,\u201d IEEE Wireless Communications Letters, vol.7, no.3, pp.420-423, 2017. 10.1109\/lwc.2017.2780128","DOI":"10.1109\/LWC.2017.2780128"},{"key":"32","doi-asserted-by":"publisher","unstructured":"[32] M. Li, Y. Hao, Y. Zhang, and M. Chen, \u201cNon-uniform pricing and resource allocation economics for hetnet based on stackelberg game,\u201d IEEE Communications Letters, vol.26, no.3, pp.632-636, 2021. 10.1109\/lcomm.2021.3137286","DOI":"10.1109\/LCOMM.2021.3137286"},{"key":"33","doi-asserted-by":"publisher","unstructured":"[33] Zhang, Y.; Liu, L.; Gu, Y.; Niyato, D.; Pan, M.; Han, Z. \u201cOffloading in software defined network at edge with information asymmetry: A contract theoretical approach,\u201d J. Signal Process. 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