DOI QR코드

DOI QR Code

A Survey on 5G Enabled Multi-Access Edge Computing for Smart Cities: Issues and Future Prospects

  • Tufail, Ali (Faculty of Computer and Information Systems, Islamic University of Madinah) ;
  • Namoun, Abdallah (Faculty of Computer and Information Systems, Islamic University of Madinah) ;
  • Alrehaili, Ahmed (Faculty of Computer and Information Systems, Islamic University of Madinah) ;
  • Ali, Arshad (Faculty of Computer and Information Systems, Islamic University of Madinah)
  • Received : 2021.06.05
  • Published : 2021.06.30

Abstract

The deployment of 5G is in full swing, with a significant yearly growth in the data traffic expected to reach 26% by the year and data consumption to reach 122 EB per month by 2022 [10]. In parallel, the idea of smart cities has been implemented by various governments and private organizations. One of the main objectives of 5G deployment is to help develop and realize smart cities. 5G can support the enhanced data delivery requirements and the mass connection requirements of a smart city environment. However, for specific high-demanding applications like tactile Internet, transportation, and augmented reality, the cloud-based 5G infrastructure cannot deliver the required quality of services. We suggest using multi-access edge computing (MEC) technology for smart cities' environments to provide the necessary support. In cloud computing, the dependency on a central server for computation and storage adds extra cost in terms of higher latency. We present a few scenarios to demonstrate how the MEC, with its distributed architecture and closer proximity to the end nodes can significantly improve the quality of services by reducing the latency. This paper has surveyed the existing work in MEC for 5G and highlights various challenges and opportunities. Moreover, we propose a unique framework based on the use of MEC for 5G in a smart city environment. This framework works at multiple levels, where each level has its own defined functionalities. The proposed framework uses the MEC and introduces edge-sub levels to keep the computing infrastructure much closer to the end nodes.

Keywords

Acknowledgement

This research work was funded by the Deanship of Research, Islamic University of Madinah, Saudi Arabia.

References

  1. https://www.smartcitiesworld.net/opinions/opinions/what5g-means-for-smart-cities
  2. Pham, Quoc-Viet & Fang, Fang & Ha, Vu & Le, Mai & Ding, Zhiguo & Le, Long & Hwang, won-Joo. (2020). A Survey of Multi-Access Edge Computing in 5G and Beyond: Fundamentals, Technology Integration, and State-of-the-Art.
  3. Belghol, Hibat Allah & Idrissi, Abdellah. (2017). MEC towards 5G: A Survey of Concepts, Use Cases, Location Tradeoffs. Transactions on Machine Learning and Artificial Intelligence. 5. 10.14738/tmlai.54.3215.
  4. Taleb, Tarik & Samdanis, K. & Mada, Badr Eddine & Flinck, Hannu & Sabella, Dario. (2017). On Multi-Access Edge Computing: A Survey of the Emerging 5G Network Edge Architecture & Orchestration. IEEE Communications Surveys & Tutorials. PP. 1-1. 10.1109/COMST.2017.2705720.
  5. Tran, Tuyen & Hajisami, Abolfazl & Pandey, Parul & Pompili, Dario. (2017). Collaborative Mobile Edge Computing in 5G Networks: New Paradigms, Scenarios, and Challenges. IEEE Communications Magazine. 55. 10.1109/MCOM.2017.1600863.
  6. Taleb, Tarik & Ksentini, Adlen & Iqbal, Muddesar & Flinck, Hannu. (2017). Mobile Edge Computing Potential in Making Cities Smarter. IEEE Communications Magazine. 55. 38-43. 10.1109/MCOM.2017.1600249CM.
  7. https://www.kaspersky.com/blog/secure-futuresmagazine/5g-securing-smart-cities/32175/
  8. https://www.govtech.com/fs/infrastructure/5G-Can-EnableSmart-Cities-If-Policymakers-Allow-It.html
  9. https://www.nec.com/en/global/insights/article/2020022501/index.html
  10. Cisco. (2019, Feb.) Cisco visual networking index: Global mobile data traffic forecast update, 2017-2022, white paper. Available At: .https://www.Cisco.com/c/dam/m/en_us/network-intelligence/serviceprovider/digital-transformation/knowledge-networkwebinars/pdfs/1213-business-services-ckn.pdf
  11. "What Is 5G Technology And How Must Businesses Prepare For It?" https://www.forbes.com/sites/bernardmarr/2019/10/25/whatis-5g-technology-and-how-must-businesses-prepare-forit/#c987e0d1758b
  12. https://gsacom.com/paper/5g-market-status-snapshotjanuary-2020/
  13. "Thinking about becoming a smart city? 10 benefits of smart cities" Available at:https://www.plantemoran.com/explore-ourthinking/insight/2018/04/thinking-about-becoming-a-smartcity-10-benefits-of-smart-cities
  14. Caragliu, A.; Del Bo, C.; Nijkamp, P. Smart cities in Europe. J. Urban Technol. 2011, 18, 65-82. https://doi.org/10.1080/10630732.2011.601117
  15. Ishida, T.; Isbister, K. Digital Cities: Technologies, Experiences, and Future Perspectives; Number 1765; Springer Science & Business Media: Berlin, Germany, 2000.
  16. Xiong, Z.; Sheng, H.; Rong, W.; Cooper, D.E. Intelligent transportation systems for smart cities: A progress review. Sci. China Inf. Sci. 2012, 55, 2908-2914. https://doi.org/10.1007/s11432-012-4725-1
  17. Bowerman, B.; Braverman, J.; Taylor, J.; Todosow, H.; von Wimmersperg, U. The vision of a smart city. In Proceedings of the 2nd International Life Extension Technology Workshop, Paris, France, 28 September 2000; Volume 28.
  18. Su, K.; Li, J.; Fu, H. Smart city and the applications. In Proceedings of the 2011 International Conference on Electronics, Communications and Control (ICECC), Zhejiang, China, 9-11 September 2011; pp. 1028-1031.
  19. Hollands, R.G. Will the real smart city please stand up? Intelligent, progressive or entrepreneurial? City 2008, 12, 303-320. https://doi.org/10.1080/13604810802479126
  20. Gubbi, J.; Buyya, R.; Marusic, S.; Palaniswami, M. Internet of Things (IoT):Avision, architectural elements, and future directions. Future Gener. Comput. Syst. 2013, 29, 1645-1660. https://doi.org/10.1016/j.future.2013.01.010
  21. Velasco, L. and Ruiz, M., 2018, July. Flexible fog computing and telecom architecture for 5G networks. In 2018 20th International Conference on Transparent Optical Networks (ICTON) (pp. 1-4). IEEE.
  22. Vilalta, R., Lopez, V., Giorgetti, A., Peng, S., Orsini, V., Velasco, L., Serral-Gracia, R., Morris, D., De Fina, S., Cugini, F. and Castoldi, P., 2017. TelcoFog: A unified flexible fog and cloud computing architecture for 5G networks. IEEE Communications Magazine, 55(8), pp.36-43. https://doi.org/10.1109/MCOM.2017.1600838
  23. Rahimi, H., Zibaeenejad, A. and Safavi, A.A., 2018, November. A novel IoT architecture based on 5G-IoT and next generation technologies. In 2018 IEEE 9th Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON) (pp. 81-88). IEEE.
  24. Rahman, M.A., Rashid, M.M., Hossain, M.S., Hassanain, E., Alhamid, M.F. and Guizani, M., 2019. Blockchain and IoT-based cognitive edge framework for sharing economy services in a smart city. IEEE Access, 7, pp.18611-18621. https://doi.org/10.1109/ACCESS.2019.2896065
  25. Hou, X., Ren, Z., Yang, K., Chen, C., Zhang, H. and Xiao, Y., 2019, April. IIoT-MEC: A novel mobile edge computing framework for 5G-enabled IIoT. In 2019 IEEE Wireless Communications and Networking Conference (WCNC) (pp. 1-7). IEEE.
  26. Carvalho, G.H., Woungang, we., Anpalagan, A. and Traore, we., 2020. When Agile Security Meets 5G. IEEE Access, 8, pp.166212-166225. https://doi.org/10.1109/ACCESS.2020.3022741
  27. Sapienza, M., Guardo, E., Cavallo, M., La Torre, G., Leombruno, G. and Tomarchio, O., 2016, May. Solving critical events through mobile edge computing: An approach for smart cities. In 2016 IEEE International Conference on Smart Computing (SMARTCOMP) (pp. 1-5). IEEE.
  28. Santos, J., Wauters, T., Volckaert, B. and De Turck, F., 2018. Fog computing: Enabling the management and orchestration of smart city applications in 5G networks. Entropy, 20(1), p.4. https://doi.org/10.3390/e20010004
  29. Sigwele, T., Hu, Y.F., Ali, M., Hou, J., Susanto, M. and Fitriawan, H., 2018, December. Intelligent and energy efficient mobile smartphone gateway for healthcare smart devices based on 5G. In 2018 IEEE Global Communications Conference (GLOBECOM) (pp. 1-7). IEEE.
  30. https://www.thalesgroup.com/en/markets/digital-identityand-security/iot/inspired/smart-cities
  31. https://www.mckinsey.com/businessfunctions/operations/our-insights/smart-cities-digitalsolutions-for-a-more-livable-future#
  32. https://www.i-scoop.eu/internet-of-things-guide/smartcities-smart-city/
  33. https://www.libelium.com/libeliumworld/top-50-iot-sensorapplications-ranking/
  34. Akhtar, M.W., Hassan, S.A., Ghaffar, R., Jung, H., Garg, S. and Hossain, M.S., 2020. The shift to 6G communications: vision and requirements. Human-centric Computing and Information Sciences, 10(1), pp.1-27. https://doi.org/10.1186/s13673-019-0205-6
  35. Mukherjee, M., Shu, L. and Wang, D., 2018. Survey of fog computing: Fundamental, network applications, and research challenges. IEEE Communications Surveys & Tutorials, 20(3), pp.1826-1857. https://doi.org/10.1109/COMST.2018.2814571
  36. Hu, Y.C., Patel, M., Sabella, D., Sprecher, N. and Young, V., 2015. Mobile edge computing-A key technology towards 5G. ETSI white paper, 11(11), pp.1-16.
  37. Kekki, S., Featherstone, W., Fang, Y., Kuure, P., Li, A., Ranjan, A., Purkayastha, D., Jiangping, F., Frydman, D., Verin, G. and Wen, K.W., 2018. MEC in 5G networks. ETSI white paper, 28, pp.1-28.
  38. ETSI, M., 2019. Multi-access edge computing (MEC) framework and reference architecture. ETSI GS MEC, 3, p.V2.
  39. OpenFog Consortium Architecture Working Group, 2016. OpenFog architecture overview. White Paper OPFWP001, 216, p.35.
  40. 3GPP Technical Specification Group Services and System Aspects; System Architecture for the 5G System, June 2019. Standard 3GPP TS 23.501 v16.1.0.
  41. Pisarov, J. and Mester, G., 2020. The Impact of 5G Technology on Life in 21st Century. IPSI BgD Transactions on Advanced Research (TAR), 16(2), pp.11-14.
  42. Gohar, A. and Nencioni, G., 2021. The Role of 5G Technologies in a Smart City: The Case for Intelligent Transportation System. Sustainability, 13(9), p.5188. https://doi.org/10.3390/su13095188
  43. Liu, Y., Peng, M., Shou, G., Chen, Y. and Chen, S., 2020. Toward edge intelligence: multi-access edge computing for 5G and Internet of things. IEEE Internet of Things Journal, 7(8), pp.6722-6747. https://doi.org/10.1109/jiot.2020.3004500
  44. https://www.cisco.com/c/en/us/solutions/computing/what-isedge-computing.html#~revenue-opportunities
  45. Aazam, M., Zeadally, S. and Harras, K.A., 2018. Fog computing architecture, evaluation, and future research directions. IEEE Communications Magazine, 56(5), pp.46-52. https://doi.org/10.1109/mcom.2018.1700707
  46. Dolui, K. and Datta, S.K., 2017, June. Comparison of edge computing implementations: Fog computing, cloudlet and mobile edge computing. In 2017 Global Internet of Things Summit (GIoTS) (pp. 1-6). IEEE.
  47. Tufail, A., Namoun, A., Sen, A.A.A., Kim, K.H., Alrehaili, A. and Ali, A., 2021. Moisture Computing-Based Internet of Vehicles (IoV) Architecture for Smart Cities. Sensors, 21(11), p.3785. https://doi.org/10.3390/s21113785
  48. He, X., Jin, R. and Dai, H., 2019. Peace: Privacy-preserving and cost-efficient task offloading for mobile-edge computing. IEEE Transactions on Wireless Communications, 19(3), pp.1814-1824. https://doi.org/10.1109/twc.2019.2958091
  49. He, T., Ciftcioglu, E.N., Wang, S. and Chan, K.S., 2017, June. Location privacy in mobile edge clouds. In 2017 IEEE 37th International Conference on Distributed Computing Systems (ICDCS) (pp. 2264-2269). IEEE.
  50. Park, J., Samarakoon, S., Bennis, M. and Debbah, M., 2019. Wireless network intelligence at the edge. Proceedings of the IEEE, 107(11), pp.2204-2239. https://doi.org/10.1109/jproc.2019.2941458
  51. Zhang, C., Patras, P. and Haddadi, H., 2019. Deep learning in mobile and wireless networking: A survey. IEEE Communications surveys & tutorials, 21(3), pp.2224-2287. https://doi.org/10.1109/COMST.2019.2904897
  52. Cao, B., Sun, Z., Zhang, J. and Gu, Y., 2021. Resource Allocation in 5G IoV Architecture Based on SDN and Fog-Cloud Computing. IEEE Transactions on Intelligent Transportation Systems, 22(6), pp.3832-3840. https://doi.org/10.1109/TITS.2020.3048844
  53. Zhuang, W., Ye, Q., Lyu, F., Cheng, N. and Ren, J., 2019. SDN/NFV-empowered future IoV with enhanced communication, computing, and caching. Proceedings of the IEEE, 108(2), pp.274-291. https://doi.org/10.1109/jproc.2019.2951169
  54. Sung, N.W., Pham, N.T., Huynh, T. and Hwang, W.J., 2013. Predictive association control for frequent handover avoidance in femtocell networks. IEEE communications letters, 17(5), pp.924-927. https://doi.org/10.1109/LCOMM.2013.031913.130127
  55. Dong, Y., Chen, Z., Fan, P. and Letaief, K.B., 2015. Mobility-aware uplink interference model for 5G heterogeneous networks. IEEE Transactions on Wireless Communications, 15(3), pp.2231-2244. https://doi.org/10.1109/TWC.2015.2500566
  56. Zhang, L., Wang, K., Xuan, D. and Yang, K., 2018. Optimal task allocation in near-far computing enhanced C-RAN for wireless big data processing. IEEE Wireless Communications, 25(1), pp.50-55. https://doi.org/10.1109/MWC.2018.1700188
  57. Dao, N.N., Lee, Y., Cho, S., Kim, E., Chung, K.S. and Keum, C., 2017, October. Multi-tier multi-access edge computing: The role for the fourth industrial revolution. In 2017 International Conference on Information and Communication Technology Convergence (ICTC) (pp. 1280-1282). IEEE.