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Multimedia Comput. Commun. Appl."],"published-print":{"date-parts":[[2019,8,31]]},"abstract":"<jats:p>The manyfold capacity magnification promised by dense 5G networks will make possible the provisioning of broadband multimedia services, including virtual reality, augmented reality, and mobile immersive video, to name a few. These new applications will coexist with classic ones and contribute to the exponential growth of multimedia services in mobile networks. At the same time, the different requirements of past and old services pose new challenges to the effective usage of 5G resources. In response to these challenges, a novel Stochastic Optimization framework for Green Multimedia Services named SOGMS is proposed herein that targets the maximization of system throughput and the minimization of energy consumption in data delivery. In particular, Lyapunov optimization is leveraged to face this optimization objective, which is formulated and decomposed into three tractable subproblems. For each subproblem, a distinct algorithm is conceived, namely quality of experience--based admission control, cooperative resource allocation, and multimedia services scheduling. Finally, extensive simulations are carried out to evaluate the proposed method against state-of-art solutions in dense 5G networks.<\/jats:p>","DOI":"10.1145\/3328996","type":"journal-article","created":{"date-parts":[[2019,9,12]],"date-time":"2019-09-12T14:22:21Z","timestamp":1568298141000},"page":"1-22","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":12,"title":["Stochastic Optimization for Green Multimedia Services in Dense 5G Networks"],"prefix":"10.1145","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8627-5587","authenticated-orcid":false,"given":"Tengfei","family":"Cao","sequence":"first","affiliation":[{"name":"Beijing University of Posts and Telecommunications, Beijing, China"}]},{"given":"Changqiao","family":"Xu","sequence":"additional","affiliation":[{"name":"Beijing University of Posts and Telecommunications, Beijing, China"}]},{"given":"Mu","family":"Wang","sequence":"additional","affiliation":[{"name":"Beijing University of Posts and Telecommunications, Beijing, China"}]},{"given":"Zhongbai","family":"Jiang","sequence":"additional","affiliation":[{"name":"Beijing University of Posts and Telecommunications, Beijing, China"}]},{"given":"Xingyan","family":"Chen","sequence":"additional","affiliation":[{"name":"Beijing University of Posts and Telecommunications, Beijing, China"}]},{"given":"Lujie","family":"Zhong","sequence":"additional","affiliation":[{"name":"Capital Normal University, Beijing, China"}]},{"given":"Luigi Alfredo","family":"Grieco","sequence":"additional","affiliation":[{"name":"Politecnico di Bari, Bari, Italy"}]}],"member":"320","published-online":{"date-parts":[[2019,9,12]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1109\/MMUL.2017.3051519"},{"key":"e_1_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1109\/MWC.2017.1600219WC"},{"volume-title":"Cisco Visual Networking Index Global Mobile Data Traffic Forecast Update","year":"2016","key":"e_1_2_1_3_1","unstructured":"Cisco2017. Cisco Visual Networking Index Global Mobile Data Traffic Forecast Update , 2016 --2021 White Paper. San Jose, CA. https:\/\/www.cisco.com\/c\/en\/us\/solutions\/collateral\/service-provider\/visual-networking-index-vni\/mobile-white-paper-c11-520862.html. Cisco2017. Cisco Visual Networking Index Global Mobile Data Traffic Forecast Update, 2016--2021 White Paper. 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Liu , A. Eryilmaz , N. B. Shroff , and E. S. Bentley . 2016. Heavy-ball: A new approach to tame delay and convergence in wireless network optimization . In Proceedings of the 2016 IEEE International Conference on Computer Communications (INFOCOM\u201916) . IEEE, Los Alamitos, CA, 1--9. J. Liu, A. Eryilmaz, N. B. Shroff, and E. S. Bentley. 2016. Heavy-ball: A new approach to tame delay and convergence in wireless network optimization. In Proceedings of the 2016 IEEE International Conference on Computer Communications (INFOCOM\u201916). IEEE, Los Alamitos, CA, 1--9."},{"key":"e_1_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1109\/JSAC.2017.2726357"},{"key":"e_1_2_1_20_1","first-page":"1","article-title":"Buffer data-driven adaptation of mobile video streaming over heterogeneous wireless networks","volume":"99","author":"Zhao P.","year":"2017","unstructured":"P. Zhao , W. Yu , X. Yang , D. Meng and L. Wang . 2017 . Buffer data-driven adaptation of mobile video streaming over heterogeneous wireless networks . IEEE Internet of Things Journal PP , 99 (2017), 1 . P. Zhao, W. Yu, X. Yang, D. Meng and L. Wang. 2017. Buffer data-driven adaptation of mobile video streaming over heterogeneous wireless networks. IEEE Internet of Things Journal PP, 99 (2017), 1.","journal-title":"IEEE Internet of Things Journal PP"},{"key":"e_1_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1109\/TMC.2017.2698469"},{"key":"e_1_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2016.2607764"},{"volume-title":"Proceedings of the 2017 IEEE 28th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC\u201917)","author":"Pervez F.","key":"e_1_2_1_23_1","unstructured":"F. Pervez , A. Adinoyi , and H. Yanikomeroglu . 2017. Efficient resource allocation for video streaming for 5G network-to-vehicle communications . 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IEEE, Los Alamitos, CA, 1--7. T. Cao, C. Xu, M. Wang, X. Chen, L. Zhong, and G. M. Muntean. 2018. Family-aware pricing strategy for accelerating video dissemination over information-centric vehicular networks. In Proceedings of the 2018 IEEE International Conference on Communications (ICC\u201918). IEEE, Los Alamitos, CA, 1--7."},{"key":"e_1_2_1_31_1","doi-asserted-by":"publisher","DOI":"10.1109\/TVT.2014.2329696"},{"key":"e_1_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.1109\/TVT.2012.2228682"},{"key":"e_1_2_1_33_1","doi-asserted-by":"crossref","unstructured":"M. J. Neely. 2010. Stochastic Network Optimization with Application to Communication and Queueing Systems. Morgan 8 Claypool.   M. J. Neely. 2010. Stochastic Network Optimization with Application to Communication and Queueing Systems. 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