A Parameterized Model for Multimedia-Content Placement of the Streaming Service on 5G Cellular Networks

Rodrigo Augusto Cardoso da Silva; Carlo Kleber da Silva Rodrigues; Vladimir Rocha

doi:10.22456/2175-2745.140750

Authors

Rodrigo Augusto Cardoso da Silva Universidade Federal do ABC (UFABC) https://orcid.org/0000-0002-9874-2605
Carlo Kleber da Silva Rodrigues Universidade Federal do ABC (UFABC) https://orcid.org/0000-0003-1231-6953
Vladimir Rocha Universidade Federal do ABC (UFABC) https://orcid.org/0000-0002-0183-2787

DOI:

https://doi.org/10.22456/2175-2745.140750

Keywords:

Multimedia Streaming, 5G Cellular Networks, Parametrized Model, CRAN Architecture

Abstract

In the context of streaming services on 5G cellular networks of CRAN architecture with MEC servers, this article proposes a parametrized linear-programming model for efficient multimedia-content placement. The model resolution is obtained using one of these two alternatives: (i) transmission-time prioritization and (ii) data-traffic prioritization. To demonstrate the model's applicability, several streaming scenarios are evaluated, each involving different object-request patterns, server-storage capacities, and access concentrations (i.e., object's popularity). Three performance metrics are assessed in the experiments: average delay, network traffic, and hit rate. The overall results show that: (i) the first alternative should be considered when the object's popularity follows a non-uniform distribution; and (ii) the second alternative is recommended when the object's popularity tends to be evenly distributed. As its main contribution, this research thus offers relevant subsidies for streaming projects in 5G cellular networks.

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References

CISCO. Cisco Annual Internet Report (2018–2023). 2020. White Paper. Disponível em: https://www.cisco.com/c/en/us/solutions/collateral/executive-perspectives/annual-internet-report/white-paper-c11-741490.html.

LI, Y. et al. Optimized Content Caching and User Association for Edge Computing in Densely Deployed Heterogeneous Networks. IEEE Transactions on Mobile Computing, v. 21, n. 6, p. 2130–2142, 2022.

SANDVINE. 2023 Global Internet Phenomena Report. 2023. White Paper. Disponível em: https://www.sandvine.com/global-internet-phenomena-report-2023.

RACHAKONDA, L. P.; SIDDULA, M.; SATHYA, V. A comprehensive study on IoT privacy and security challenges with focus on spectrum sharing in Next-Generation networks (5G/6G/beyond). High-Confidence Computing, v. 4, n. 2, p. 100220, 2024. ISSN 2667-2952. Disponível em: https://www.sciencedirect.com/science/article/pii/S2667295224000230.

SHRAMA, L.; JAVALI, A.; ROUTRAY, S. K. An Overview of High Speed Streaming in 5G. In: 2020 International Conference on Inventive Computation Technologies (ICICT). [S.l.: s.n.], 2020. p. 557–562.

LIN, P. et al. Joint Optimization of Preference-Aware Caching and Content Migration in Cost-Efficient Mobile Edge Networks. IEEE Transactions on Wireless Communications, p. 1–1, 2023.

LI, K. et al. Coordination of Macro Base Stations for 5G Network with User Clustering. Sensors, v. 21, n. 16, 2021. Disponível em: https://www.mdpi.com/1424-8220/21/16/5501.

PATTARANANTAKUL, M.; VORAKULPIPAT, C.; TAKAHASHI, T. Service Function Chaining security survey: Addressing security challenges and threats. Computer Networks, v. 221, p. 109484, 2023. ISSN 1389-1286. Disponível em: https://www.sciencedirect.com/science/article/pii/S1389128622005187.

BHANDARI, A. et al. Latency optimized C-RAN in optical backhaul and RF fronthaul architecture for beyond 5G network: A comprehensive survey. Computer Networks, v. 247, p. 110459, 2024. ISSN 1389-1286. Disponível em: https://www.sciencedirect.com/science/article/pii/S1389128624002913.

AGUILAR-ARMIJO, J.; TIMMERER, C.; HELLWAGNER, H. SPACE: Segment Prefetching and Caching at the Edge for Adaptive Video Streaming. IEEE Access, v. 11, p. 21783–21798, 2023.

SARAH, A.; NENCIONI, G.; KHAN, M. M. I. Resource Allocation in Multi-access Edge Computing for 5G-and-beyond networks. Computer Networks, v. 227, p. 109720, 2023. Disponível em: https://www.sciencedirect.com/science/article/pii/S1389128623001652.

LIANG, B.; GREGORY, M. A.; LI, S. Multi-access edge computing fundamentals, services, enablers and challenges: A complete survey. Journal of Network and Computer Applications, v. 199, p. 103308, 2022. Disponível em: https://www.sciencedirect.com/science/article/pii/S1084804521002976.

RODOSHI, R. T.; KIM, T.; CHOI, W. Fuzzy Logic and Accelerated Reinforcement Learning-Based User Association for Dense C-RANs. IEEE Access, v. 9, p. 117910–117924, 2021.

HOSSAIN, M. F. et al. Recent research in cloud radio access network (C-RAN) for 5G cellular systems - A survey. Journal of Network and Computer Applications, v. 139, p. 31–48, 2019. ISSN 1084-8045. Disponível em: https://www.sciencedirect.com/science/article/pii/S1084804519301432.

PANA, V. S.; BABALOLA, O. P.; BALYAN, V. 5G radio access networks: A survey. Array, v. 14, p. 100170, 2022. ISSN 2590-0056. Disponível em: https://www.sciencedirect.com/science/article/pii/S2590005622000315.

ALAM, M. J. et al. An overview of LTE/LTE-A heterogeneous networks for 5G and beyond. Transactions on Emerging Telecommunications Technologies, Wiley Online Library, p. e4806, 2023.

SILVEIRA, L. B. et al. Tutorial on communication between access networks and the 5G core. Computer Networks, v. 216, p. 109301, 2022. ISSN 1389-1286. Disponível em: https://www.sciencedirect.com/science/article/pii/S1389128622003528.

ULLAH, Y. et al. A Survey on Handover and Mobility Management in 5G HetNets: Current State, Challenges, and Future Directions. Sensors, MDPI AG, v. 23, n. 11, p. 5081, May 2023. ISSN 1424-8220. Disponível em: http://dx.doi.org/10.3390/s23115081.

REHMAN, A. U.; ROSLEE, M. B.; JIAT, T. J. A Survey of Handover Management in Mobile HetNets: Current Challenges and Future Directions. Applied Sciences, MDPI AG, v. 13, n. 5, p. 3367, Mar 2023. ISSN 2076-3417. Disponível em: http://dx.doi.org/10.3390/app13053367.

LIN, C.-H. et al. Energy Efficient Fog RAN (F-RAN) with Flexible BBU Resource Assignment for Latency Aware Mobile Edge Computing (MEC) Services. In: 2019 IEEE 90th Vehicular Technology Conference (VTC2019-Fall). [S.l.: s.n.], 2019. p. 1–6.

TIAN, F.; ZHANG, P.; YAN, Z. A Survey on C-RAN Security. IEEE Access, v. 5, p. 13372–13386, 2017.

NIU, B. et al. A Dynamic Resource Sharing Mechanism for Cloud Radio Access Networks. IEEE Transactions on Wireless Communications, v. 15, n. 12, p. 8325–8338, 2016.

MEI, H.; PENG, L. Flexible functional split for cost-efficient C-RAN. Computer Communications, v. 161, p. 368–374, 2020. ISSN 0140-3664. Disponível em: https://www.sciencedirect.com/science/article/pii/S0140366420318417.

MANGLA, C. et al. Mitigating 5G security challenges for next-gen industry using quantum computing. Journal of King Saud University - Computer and Information Sciences, v. 35, n. 6, p. 101334, 2023. ISSN 1319-1578. Disponível em: https://www.sciencedirect.com/science/article/pii/S1319157822002373.

DAO, N.-N. et al. A review on new technologies in 3GPP standards for 5G access and beyond. Computer Networks, v. 245, p. 110370, 2024. ISSN 1389-1286. Disponível em: https://www.sciencedirect.com/science/article/pii/S1389128624002020.

WU, J. et al. Cloud radio access network (C-RAN): a primer. IEEE Network, v. 29, n. 1, p. 35–41, 2015.

SURYAPRAKASH, V.; ROST, P.; FETTWEIS, G. Are heterogeneous cloud-based radio access networks cost effective? IEEE Journal on Selected Areas in Communications, v. 33, n. 10, p. 2239–2251, 2015.

ALHUMAIMA, R. S.; KHAN, M.; AL-RAWESHIDY, H. S. Component and parameterised power model for cloud radio access network. IET Communications, v. 10, n. 7, p. 745–752, 2016.

BASSOLI, R.; RENZO, M. D.; GRANELLI, F. Analytical energy-efficient planning of 5G cloud radio access network. In: 2017 IEEE International Conference on Communications (ICC). [S.l.: s.n.], 2017. p. 1–4.

CHECKO, A. et al. Cloud RAN for Mobile Networks—A Technology Overview. IEEE Communications Surveys & Tutorials, v. 17, n. 1, p. 405–426, 2015.

SIMEONE, O. et al. Cloud radio access network: Virtualizing wireless access for dense heterogeneous systems. Journal of Communications and Networks, v. 18, n. 2, p. 135–149, 2016.

PENG, M. et al. Recent Advances in Cloud Radio Access Networks: System Architectures, Key Techniques, and Open Issues. IEEE Communications Surveys & Tutorials, v. 18, n. 3, p. 2282–2308, 2016.

KANI, J. ichi; KUWANO, S.; TERADA, J. Options for future mobile backhaul and fronthaul. Optical Fiber Technology, v. 26, p. 42–49, 2015. Next Generation Access Networks. Disponível em: https://www.sciencedirect.com/science/article/pii/S1068520015000954.

SAFAVAT, S.; SAPAVATH, N. N.; RAWAT, D. B. Recent advances in mobile edge computing and content caching. Digital Communications and Networks, v. 6, n. 2, p. 189–194, 2020. ISSN 2352-8648. Disponível em: https://www.sciencedirect.com/science/article/pii/S2352864819300227.

NARAYANAN, A. et al. A First Look at Commercial 5G Performance on Smartphones. In: Proceedings of The Web Conference 2020. New York, NY, USA: Association for Computing Machinery, 2020. (WWW ’20), p. 894–905. Disponível em: https://doi.org/10.1145/3366423.3380169.

XU, D. et al. Understanding Operational 5G: A First Measurement Study on Its Coverage, Performance and Energy Consumption. In: Proceedings of the Annual Conference of the ACM Special Interest Group on Data Communication on the Applications, Technologies, Architectures, and Protocols for Computer Communication. New York, NY, USA: [s.n.], 2020. p. 479–494.

PRERNA, D.; TEKCHANDANI, R.; KUMAR, N. Device-to-device content caching techniques in 5G: A taxonomy, solutions, and challenges. Computer Communications, v. 153, p. 48–84, 2020. ISSN 0140-3664. Disponível em: https://www.sciencedirect.com/science/article/pii/S0140366419318225.

AYTAC, K. N. et al. Device-to-device caching for video content delivery. In: 2017 IEEE International Black Sea Conference on Communications and Networking (BlackSeaCom). [S.l.: s.n.], 2017. p. 1–2.

BANIATA, M. et al. Energy-Balancing Unequal Concentric Chain Clustering (MIMO-UCC) Protocol for IoT System in 5G Environment. In: Proceedings of the 2018 Conference on Research in Adaptive and Convergent Systems. New York, NY, USA: Association for Computing Machinery, 2018. (RACS ’18), p. 68–74. ISBN 9781450358859. Disponível em: https://doi.org/10.1145/3264746.3264747.

GONG, Y.; WANG, J.; LAI, G. Energy-efficient Query-Driven Clustering protocol for WSNs on 5G infrastructure. Energy Reports, v. 8, p. 11446–11455, 2022. ISSN 2352-4847. Disponível em: https://www.sciencedirect.com/science/article/pii/S235248472201719X.

TENG, W. et al. Content Placement and User Association for Delay Minimization in Small Cell Networks. IEEE Transactions on Vehicular Technology, v. 68, n. 10, p. 10201–10215, 2019.

WANG, Y. et al. Joint Caching Placement and User Association for Minimizing User Download Delay. IEEE Access, v. 4, p. 8625–8633, 2016.

WU, H. et al. Energy and Delay Optimization for Cache-Enabled Dense Small Cell Networks. IEEE Transactions on Vehicular Technology, v. 69, n. 7, p. 7663–7678, 2020.

LIU, Y. et al. Joint User Association and Caching in Wireless Heterogeneous Networks with Backhaul. In: ICC 2021 - IEEE International Conference on Communications. [S.l.: s.n.], 2021. p. 1–6.

MOLNER, N. et al. Optimization of an integrated fronthaul/backhaul network under path and delay constraints. Ad Hoc Networks, v. 83, p. 41–54, 2019. Disponível em: https://www.sciencedirect.com/science/article/pii/S1570870518306206.

NAUDTS, B. et al. How can a mobile service provider reduce costs with software-defined networking? International Journal of Network Management, Wiley Online Library, v. 26, n. 1, p. 56–72, 2016.

WIKIPÉDIA. Morumbi (distrito de São Paulo). 2023. ONLINE. Disponível em: https://pt.wikipedia.org/wiki/Morumbi_(distrito_de_S%C3%A3o_Paulo).

COOK, S. Netflix statistics & facts that define the company’s dominance in 2023. 2023. ONLINE. Disponível em: https://www.comparitech.com/blog/vpn-privacy/netflix-statistics-facts-figures/.

STOLL, J. Countries with most content available on Netflix worldwide as of March 2023. 2023. ONLINE. Disponível em: https://www.statista.com/statistics/1013571/netflix-library-size-worldwide/.

WANG, T. et al. Estimating Video Popularity From Past Request Arrival Times in a VoD System. IEEE Access, v. 8, p. 19934–19947, 2020. Disponível em: https://ieeexplore.ieee.org/document/8959235.

CHERKASOVA, L.; GUPTA, M. Analysis of enterprise media server workloads: access patterns, locality, content evolution, and rates of change. IEEE/ACM Transactions on Networking, v. 12, n. 5, p. 781–794, 2004. Disponível em: https://ieeexplore.ieee.org/document/1344003.

MITRA, S. et al. Characterizing Web-Based Video Sharing Workloads. ACM Trans. Web, Association for Computing Machinery, New York, NY, USA, v. 5, n. 2, may 2011. ISSN 1559-1131. Disponível em: https://doi.org/10.1145/1961659.1961662.

ALMEIDA, J. M. et al. Analysis of educational media server workloads. In: Proceedings of the 11th International Workshop on Network and Operating Systems Support for Digital Audio and Video. New York, NY, USA: Association for Computing Machinery, 2001. (NOSSDAV ’01), p. 21–30. ISBN 1581133707. Disponível em: https://doi.org/10.1145/378344.378348.

Gurobi Optimization. Gurobi Optimizer Reference Manual - Version 11.0. 2024. ONLINE. Disponível em: https://www.gurobi.com/documentation/current/refman/index.html.

YIN, J. et al. Nefis: A network coding based flexible device-to-device video streaming scheme. Journal of Network and Computer Applications, v. 227, p. 103892, 2024. ISSN 1084-8045. Disponível em: https://www.sciencedirect.com/science/article/pii/S1084804524000699.

JIMÉNEZ-SORIA, D.; MARTÍN-VEGA, F. J.; AGUAYO-TORRES, M. C. Coordinated Multicast/Unicast Transmission on 5G: A Novel Approach for Linear Broadcasting. Wireless Personal Communications, v. 121, n. 2, p. 1273–1287, Nov 2021. ISSN 1572-834X. Disponível em: https://doi.org/10.1007/s11277-021-09057-z.