| dc.identifier.citation | [1] Sagar Arora and Adlen Ksentini. 2021. Dynamic Resource Allocation and Placement of Cloud Native Network Services. In <i>IEEE Int. Conf. Commun. (ICC)</i>. 1–6. [2] Dario Bega et al. 2019. DeepCog: Cognitive Network Management in Sliced 5G Networks with Deep Learning. In <i>Proc. of IEEE INFOCOM</i>. 1–9. [3] Dario Bega, Marco Gramaglia, Albert Banchs, Vincenzo Sciancalepore, Konstantinos Samdanis, and Xavier Costa-Perez. 2017. Optimising 5G infrastructure markets: The business of network slicing. In <i>Proc. of IEEE INFOCOM</i>. 1–9. [4] Walid Ben-Ameur, Lorela Cano, and Tijani Chahed. 2021. A framework for joint admission control, resource allocation and pricing for network slicing in 5G. In <i>2021 IEEE Global Communications Conf. (GLOBECOM)</i>. 1–6. [5] Mans Burman and Magnus Gall. 2022. Ericsson and Red Hat empower service providers to build multi-vendor networks. [6] Pablo Caballero, Albert Banchs, Gustavo de Veciana, and Xavier Costa-Pérez. 2017. Multi-Tenant Radio Access Network Slicing: Statistical Multiplexing of Spatial Loads. <i>IEEE/ACM Transactions on Networking</i> 25, 5 (2017), 3044–3058. [7] Pablo Caballero, Albert Banchs, Gustavo de Veciana, Xavier Costa-Pérez, and Arturo Azcorra. 2018. Network Slicing for Guaranteed Rate Services: Admission Control and Resource Allocation Games. <i>IEEE Transactions on Wireless Communications</i> 17, 10 (2018), 6419–6432. [8] Sajjad Gholamipour, Behzad Akbari, Nader Mokari, Mohammad Mahdi Tajiki, and Eduard Axel Jorswieck. 2021. Online Admission Control and Resource Allocation in Network Slicing under Demand Uncertainties. [9] Dimitris Giannopoulos, Panagiotis Papaioannou, Christos Tranoris, and Spyros Denazis. 2021. Monitoring as a Service over a 5G Network Slice. In <i>Joint European Conf. on Networks and Commun. & 6G Summit (EuCNC/6G Summit)</i>. 329–334. [10] Bin Han, Vincenzo Sciancalepore, Di Feng, Xavier Costa-Perez, and Hans D. Schotten. 2019. A Utility-Driven Multi-Queue Admission Control Solution for Network Slicing. In <i>Proc. of IEEE INFOCOM</i>. 55–63. [11] Yuxiu Hua, Rongpeng Li, Zhifeng Zhao, Xianfu Chen, and Honggang Zhang. 2020. GAN-Powered Deep Distributional Reinforcement Learning for Resource Management in Network Slicing. <i>IEEE J. Selected Areas in Communications</i> 38, 2 (2020), 334–349. [12] Johanna Andrea Hurtado Sánchez, Katherine Casilimas, and Oscar Mauricio Caicedo Rendon. 2022. Deep Reinforcement Learning for Resource Management on Network Slicing: A Survey. <i>Sensors</i> 22, 8 (2022). 1424-8220 [13] Jaehoon Koo, Veena B. Mendiratta, Muntasir Raihan Rahman, and Anwar Walid. 2019. Deep Reinforcement Learning for Network Slicing with Heterogeneous Resource Requirements and Time Varying Traffic Dynamics. In <i>Int. Conf. on Network and Service Management (CNSM)</i>. 1–5. [14] Qiang Liu, Tao Han, and Ephraim Moges. 2020. EdgeSlice: Slicing Wireless Edge Computing Network with Decentralized Deep Reinforcement Learning. In <i>IEEE Int. Conf. on Distributed Computing Systems (ICDCS)</i>. 234–244. [15] Minghui Liwang, Xianbin Wang, and Ruitao Chen. 2022. Computing Resource Provisioning at the Edge: An Overbooking-Enabled Trading Paradigm. <i>IEEE Wireless Commun.</i> 29, 5 (2022), 68–76. <a href="https://doi.org/10.1109/MWC.104.2100380">https://doi.org/10.1109/MWC.104.2100380</a> [16] Leonardo Lo Schiavo, Marco Fiore, Marco Gramaglia, Albert Banchs, and Xavier Costa-Perez. 2022. Forecasting for Network Management with Joint Statistical Modelling and Machine Learning. (2022). [17] Ziyue Luo, Chuan Wu, Zongpeng Li, and Wei Zhou. 2019. Scaling Geo-Distributed Network Function Chains: A Prediction and Learning Framework. <i>IEEE J. Selected Areas in Communications</i> 37, 8 (2019), 1838–1850. [18] Quang-Trung Luu, Sylvaine Kerboeuf, and Michel Kieffer. 2021. Uncertainty-Aware Resource Provisioning for Network Slicing. <i>IEEE Transactions on Network and Service Management</i> 18, 1 (2021), 79–93. [19] Spyros Makridakis, Evangelos Spiliotis, and Vassilios Assimakopoulos. 2020. The M4 Competition: 100,000 time series and 61 forecasting methods. <i>Int. Journal of Forecasting</i> 36, 1 (2020), 54 – 74. 0169-2070 <a href="https://doi.org/10.1016/j.ijforecast.2019.04.014">https://doi.org/10.1016/j.ijforecast.2019.04.014</a> [20] Cristina Marquez, Marco Gramaglia, Marco Fiore, Albert Banchs, and Xavier Costa-Pérez. 2019. Resource Sharing Efficiency in Network Slicing. <i>IEEE Transactions on Network and Service Management</i> 16, 3 (2019), 909–923. [21] S. Martello. 1990. Knapsack Problems: Algorithms and Computer Implementations. <i>Wiley-Interscience series in discrete mathematics and optimiza tion</i> (1990). [22] S. Martello and P. Toth. 1990. <i>Knapsack Problems: Algorithms and Computer Implementations</i>. Wiley. lc90012279 <a href="https://books.google.es/books?id=0dhQAAAAMAAJ">https://books.google.es/books?id=0dhQAAAAMAAJ</a> [23] Felix Patzelt. 2022. Colored Noise. <a href="https://github.com/felixpatzelt/colorednoise">https://github.com/felixpatzelt/colorednoise</a>. [24] Adrián Pino, Pouria Khodashenas, Xavier Hesselbach, Estefanía Coronado, and Shuaib Siddiqui. 2021. Validation and Benchmarking of CNFs in OSM for pure Cloud Native applications in 5G and beyond. In <i>2021 Int. Conf. on Computer Communications and Networks (ICCCN)</i>. 1–9. [25] JE Rachid and J Erfanian. 2015. NGMN 5G Initiative White Paper. [26] Josep Xavier Salvat, Lanfranco Zanzi, Andres Garcia-Saavedra, Vincenzo Sciancalepore, and Xavier Costa-Perez. 2018. Overbooking Network Slices through Yield-Driven End-to-End Orchestration. In <i>Proc. Int. Conf. Emerging Networking EXperiments and Technologies (CoNEXT)</i>. 353–365. [27] Shivani Saxena and Krishna M. Sivalingam. 2022. Slice admission control using overbooking for enhancing provider revenue in 5G Networks. In <i>NOMS 2022-2022 IEEE/IFIP Network Operations and Management Symposium</i>. 1–7. [28] Conor Sexton, Nicola Marchetti, and Luiz A. DaSilva. 2020. On Provisioning Slices and Overbooking Resources in Service Tailored Networks of the Future. <i>IEEE/ACM Transactions on Networking</i> 28, 5 (2020), 2106–2119. [29] Syed Danial Ali Shah, Mark A. Gregory, and Shuo Li. 2021. Cloud-Native Network Slicing Using Software Defined Networking Based Multi-Access Edge Computing: A Survey. <i>IEEE Access</i> 9 (2021), 10903–10924. [30] Kalyan T. Talluri and Garrett Van Ryzin. 2004. <i>The theory and practice of revenue management</i>. Vol. 1. Springer. [31] Zhiqing Tang, Fuming Zhang, Xiaojie Zhou, Weijia Jia, and Wei Zhao. 2022. Pricing Model for Dynamic Resource Overbooking in Edge Computing. <i>IEEE Transactions on Cloud Computing</i> (2022). [32] The Linux Foundation. 2022. The Linux Foundation and Google Cloud Launch Nephio to Enable and Simplify Cloud Native Automation of Telecom Network Functions. Consulted on March 10th 2023. [33] Denis Tikunov and Toshikazu Nishimura. 2007. Traffic prediction for mobile network using Holt-Winter’s exponential smoothing. In <i>Int. Conf. on Software, Telecommunications and Computer Networks</i>. IEEE, 1–5. [34] Sebastian Troia, Rodolfo Alvizu, and Guido Maier. 2019. Reinforcement Learning for Service Function Chain Reconfiguration in NFV-SDN Metro-Core Optical Networks. <i>IEEE Access</i> 7 (2019), 167944–167957. [35] Nguyen Van Huynh, Dinh Thai Hoang, Diep N. Nguyen, and Eryk Dutkiewicz. 2019. Optimal and Fast Real-Time Resource Slicing With Deep Dueling Neural Networks. <i>IEEE J. Selected Areas in Communications</i> 37, 6 (2019), 1455–1470. [36] Lanfranco Zanzi, Josep Xavier Salvat, Vincenzo Sciancalepore, Andres Garcia Saavedra, and Xavier Costa-Perez. 2018. Overbooking Network Slices End-to-End: Implementation and Demonstration. In <i>Proc. of ACM SIGCOMM</i>. 144–146. [37] Jiaxiao Zheng, Pablo Caballero, Gustavo de Veciana, Seung Jun Baek, and Albert Banchs. 2018. Statistical Multiplexing and Traffic Shaping Games for Network Slicing. <i>IEEE/ACM Transactions on Networking</i> 26, 6 (2018), 2528–2541. <a href="https://doi.org/10.1109/TNET.2018.2870184">https://doi.org/10.1109/TNET.2018.2870184</a> [38] Xuan Zhou, Rongpeng Li, Tao Chen, and Honggang Zhang. 2016. Network slicing as a service: enabling enterprises' own software-defined cellular networks. <i>IEEE Communications Magazine</i> 54, 7 (2016), 146–153. | es |
