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QoS-aware 5G component selection for content delivery in multi-access edge computing

Published: 17 December 2021 Publication History

Abstract

The demand for content such as multimedia services with stringent latency requirements has proliferated significantly, posing heavy backhaul congestion in mobile networks. The integration of Multi-access Edge Computing (MEC) and 5G network is an emerging solution that alleviates the backhaul congestion to meet QoS requirements such as ultra-low latency, ultra-high reliability, and continuous connectivity to support various latency-critical applications for user equipment (UE). Content caching can markedly augment QoS for UEs by increasing the availability of popular content. However, uncertainties originating from user mobility cause the most challenging barrier in deciding content routes for UEs that lead to minimum latency. Considering the 5G-enabled MEC components, it is critical to select the optimal 5G components, representing content routes from Edge Application Servers (EASs) to UEs, that enhances QoS for the UEs with uncertain mobility patterns by reducing frequent handover (path reallocation). To this aim, we study the component selection for QoS-aware content delivery in 5G-enabled MEC. We first formulate an integer programming (IP) optimization model to obtain the optimal content routing decisions. As this problem is NP-hard, we tackle its intractability by designing an efficient online learning approach, called Q-CSCD, to achieve a bounded performance. Q-CSCD learns the optimal component selection for UEs and autonomously makes decisions to minimize latency for content delivery. We conduct extensive experiments based on a real-world dataset to validate the effectiveness of our proposed algorithm. The results reveal that Q-CSCD leads to low latency and handover ratio in a reasonable time with a reduced regret over time.

References

[1]
2009. Latency Is Everywhere And It Costs You Sales - How To Crush It. Available: http://highscalability.com/latency-everywhere-and-it-costs-you-sales-how-crush-it.
[2]
2021. Thousandeyes. Available: https://www.thousandeyes.com/.
[3]
Peter Auer, Nicolo Cesa-Bianchi, and Paul Fischer. 2002. Finite-time analysis of the multiarmed bandit problem. Machine learning 47, 2 (2002), 235--256.
[4]
Peter Auer, Nicolo Cesa-Bianchi, Yoav Freund, and Robert E Schapire. 2002. The nonstochastic multiarmed bandit problem. SIAM journal on computing 32, 1 (2002), 48--77.
[5]
Ejder Bastug, Mehdi Bennis, and Mérouane Debbah. 2014. Living on the edge: The role of proactive caching in 5G wireless networks. IEEE Communications Magazine 52, 8 (2014), 82--89.
[6]
Pol Blasco and Deniz Gündüz. 2014. Learning-based optimization of cache content in a small cell base station. In Proc. of the IEEE International Conference on Communications (ICC). 1897--1903.
[7]
Cisco. 2016. Internet of Things. Available: https://www.cisco.com/c/en/us/products/collateral/se/internet-of-things/at-a-glance-c45-731471.pdf.
[8]
GMDT Forecast. 2019. Cisco visual networking index: global mobile data traffic forecast update, 2017--2022. Update 2017 (2019), 2022.
[9]
Shaoyong Guo, Sujie Shao, Yao Wang, and Hui Yang. 2017. Cross stratum resources protection in fog-computing-based radio over fiber networks for 5G services. Optical Fiber Technology 37 (2017), 61--68.
[10]
Najmul Hassan, Kok-Lim Alvin Yau, and Celimuge Wu. 2019. Edge computing in 5G: A review. IEEE Access 7 (2019), 127276--127289.
[11]
Tingting Hou, Gang Feng, Shuang Qin, and Wei Jiang. 2018. Proactive content caching by exploiting transfer learning for mobile edge computing. International Journal of Communication Systems 31, 11 (2018), e3706.
[12]
Yun Chao Hu, Milan Patel, Dario Sabella, Nurit Sprecher, and Valerie Young. 2015. Mobile edge computing---A key technology towards 5G. ETSI white paper 11, 11 (2015), 1--16.
[13]
IBM. 2009. Concert Technology version 12.1 C++ API Reference Manual. Available: ftp://public.dhe.ibm.com/software/websphere/ilog/docs/optimization/cplex/refcppcplex.pdf. Accessed: 2019-05-25.
[14]
Michael N Katehakis and Arthur F Veinott Jr. 1987. The multi-armed bandit problem: decomposition and computation. Mathematics of Operations Research 12, 2 (1987), 262--268.
[15]
Abbas Kiani and Nirwan Ansari. 2018. Edge computing aware NOMA for 5G networks. IEEE Internet of Things Journal 5, 2 (2018), 1299--1306.
[16]
Stojan Kitanov and Toni Janevski. 2017. Energy efficiency of Fog Computing and Networking services in 5G networks. In Proc. of the IEEE EUROCON 17th International Conference on Smart Technologies. 491--494.
[17]
Dong Liu and Chenyang Yang. 2017. Optimizing caching policy at base stations by exploiting user preference and spatial locality. arXiv preprint arXiv:1710.09983 (2017).
[18]
Erfan Farhangi Maleki, Lena Mashayekhy, and Seyed Morteza Nabavinejad. 2021. Mobility-Aware Computation Offloading in Edge Computing using Machine Learning. IEEE Transactions on Mobile Computing (2021).
[19]
Evangelos K Markakis, Kimon Karras, Anargyros Sideris, George Alexiou, and Evangelos Pallis. 2017. Computing, caching, and communication at the edge: The cornerstone for building a versatile 5G ecosystem. IEEE Communications Magazine 55, 11 (2017), 152--157.
[20]
Milan Patel, Brian Naughton, Caroline Chan, Nurit Sprecher, Sadayuki Abeta, Adrian Neal, et al. 2014. Mobile-edge computing introductory technical white paper. White paper, mobile-edge computing (MEC) industry initiative 29 (2014), 854--864.
[21]
Jian Qiao, Yejun He, and Xuemin Sherman Shen. 2016. Proactive caching for mobile video streaming in millimeter wave 5G networks. IEEE Transactions on Wireless Communications 15, 10 (2016), 7187--7198.
[22]
Bhaskar Prasad Rimal, Dung Pham Van, and Martin Maier. 2017. Mobile edge computing empowered fiber-wireless access networks in the 5G era. IEEE Communications Magazine 55, 2 (2017), 192--200.
[23]
Ruben Solozabal, Aitor Sanchoyerto, Eneko Atxutegi, Bego Blanco, Jose Oscar Fajardo, and Fidel Liberal. 2018. Exploitation of mobile edge computing in 5G distributed mission-critical push-to-talk service deployment. IEEE Access 6 (2018), 37665--37675.
[24]
Yuxuan Sun, Sheng Zhou, and Jie Xu. 2017. EMM: Energy-aware mobility management for mobile edge computing in ultra dense networks. IEEE Journal on Selected Areas in Communications 35, 11 (2017), 2637--2646.
[25]
Shiyu Tang, Ali Alnoman, Alagan Anpalagan, and Isaac Woungang. 2018. A user-centric cooperative edge caching scheme for minimizing delay in 5G content delivery networks. Transactions on Emerging Telecommunications Technologies 29, 8 (2018), e3461.
[26]
Takahito Yoshizawa, Sheeba Backia Mary Baskaran, and Andreas Kunz. 2019. Overview of 5g urllc system and security aspects in 3gpp. In 2019 IEEE Conference on Standards for Communications and Networking (CSCN). IEEE, 1--5.
[27]
Ke Zhang, Supeng Leng, Yejun He, Sabita Maharjan, and Yan Zhang. 2018. Co-operative content caching in 5G networks with mobile edge computing. IEEE Wireless Communications 25, 3 (2018), 80--87.

Cited By

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  • (2024)Integrating Multi-Access Edge Computing (MEC) into Open 5G CoreTelecom10.3390/telecom50200225:2(433-450)Online publication date: 3-Jun-2024
  • (2024)QoS-Aware Content Delivery in 5G-Enabled Edge Computing: Learning-Based ApproachesIEEE Transactions on Mobile Computing10.1109/TMC.2024.336314323:10(9324-9336)Online publication date: Oct-2024
  • (2023)Multi-User Dynamic Computation Offloading and Resource Allocation in 5G MEC Heterogeneous Networks with Static and Dynamic SubchannelsIEEE Transactions on Vehicular Technology10.1109/TVT.2023.3285069(1-16)Online publication date: 2023

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      cover image ACM Conferences
      UCC '21: Proceedings of the 14th IEEE/ACM International Conference on Utility and Cloud Computing
      December 2021
      214 pages
      ISBN:9781450385640
      DOI:10.1145/3468737
      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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      Published: 17 December 2021

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      Author Tags

      1. 5G
      2. content delivery
      3. mobility
      4. multi-access edge computing
      5. multi-armed bandit

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      UCC '21 Paper Acceptance Rate 21 of 62 submissions, 34%;
      Overall Acceptance Rate 38 of 125 submissions, 30%

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      Cited By

      View all
      • (2024)Integrating Multi-Access Edge Computing (MEC) into Open 5G CoreTelecom10.3390/telecom50200225:2(433-450)Online publication date: 3-Jun-2024
      • (2024)QoS-Aware Content Delivery in 5G-Enabled Edge Computing: Learning-Based ApproachesIEEE Transactions on Mobile Computing10.1109/TMC.2024.336314323:10(9324-9336)Online publication date: Oct-2024
      • (2023)Multi-User Dynamic Computation Offloading and Resource Allocation in 5G MEC Heterogeneous Networks with Static and Dynamic SubchannelsIEEE Transactions on Vehicular Technology10.1109/TVT.2023.3285069(1-16)Online publication date: 2023
      • (2022)Physics-Inspired Mobile Cloudlet Placement in Next-Generation Edge Networks2022 IEEE International Conference on Edge Computing and Communications (EDGE)10.1109/EDGE55608.2022.00031(159-168)Online publication date: Jul-2022

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