MEC towards 5G: A Survey of Concepts, Use Cases, Location Tradeoffs
In recent years, there has been a new trend to push everything to a centralized cloud, triggered by virtualization and pushed by the need to reduce costs and increase suppleness. In the process, mobile operators and industry players forgot how prominent the location of the functionality is to performance, optimal use of network resources and user experience. As they progressively grasp the influence of location in wireless networks and specifically in virtualized networks they start to look for efficient ways to deploy network taking in consideration those metrics. On the one hand Distributed Cloud RAN (DC-RAN) which consists in deploying Base Band Units (BBUs) in distributed way instead of pooling the units at centralized data center and Multiple-access Edge Computing (MEC), Previously known as Mobile Edge Computing which consists in mixing the IT & Telco domains and bringing their capabilities within the close proximity of mobile subscribers to better serve them are gaining acceptance in mobile networks. On the other hand, Software Defined Networking (SDN) and Network Function Virtualization (NFV), two promising concepts are expected to take mobile networks to a high level of agility. While SDN is based on the separation of control and data planes, NFV separates software from hardware enabling flexible network deployment and dynamic operation. Virtualization, originally used as the support for shifting to the centralized cloud, is even more basic in permitting hybrid models because it offers service providers the chance to choose a location, hardware, and software separately to optimize end-to-end network performance and Quality of Experience (QoE). In this perspective, NFV, SDN, DC-RAN, and MEC in distinct but in complementary ways man up the necessity to put processing and storage where it’s suitable to preserve a healthful harmony between what lingers centralized and what have to be distributed to the edge based on parameters such as applications, traffic type, and network conditions. In this paper, we will present MEC use cases that have gained an attraction to date and we will shed the light on the importance of the edge location and criteria to take in consideration while deploying MEC within network along with the MEC location tradeoffs.
(1) INTERDIGITAL, “Putting Together the Pieces of the 5G Puzzle,” http://www.interdigital.com/ : White paper, October 2016, p.2.
(2) Cisco VNI Mobile, “Cisco Visual Networking Index: Global Mobile Data Traffic Forecast Update, 20162021,” http://www.cisco.com: White paper, February 2017, pp.1-28.
(3) G. A. Lewis, “Mobile computing at the edge (keynote),” in Proceedings
of the 1st International Conference on Mobile Software Engineering and Systems. ACM, 2014, pp. 69–70.
(4) N. Sprecher, “MEC Activity Report 2015,” https://portal.etsi.org/.
(5) M. Patel, J. Joubert, J. Ramos, N. Sprecher, S. Abeta, A. Neal “Mobile-Edge Computing – Introductory Technical White Paper,” https://portal.etsi.org/:White paper, September 2014.
(6) D. Sabella, N. Sprecher, M. Patel, V. Young, Y. Chao Hu “Mobile Edge Computing a key technology towards 5G,” http://www.etsi.org/: Whitepaper, September 2015.
(7) E. Borcoci, “Fog Computing, Mobile Edge Computing, Cloudlets which one?.” https://www.iaria.org/: SoftNet 2016 Conference, August 2016.
(8) INTERDIGITAL, “What the MEC? An Architecture for 5G,” http://www.interdigital.com/ : White paper, December 2016.
(9) J. O. Fajardo, F. Liberal, I. Giannoulakis, E. Kafetzakis, V.
Pii, I. Trajkovska, T. M. Bohnert, L. Goratti, R. Riggio, J. G. Lloreda et al.,“Introducing mobile edge computing capabilities through distributed 5g cloud enabled small cells,” Mobile networks
and applications, vol. 21, no. 4, pp. 564–574, 2016.
(10) O. Salman, I. Elhajj, A. Kayssi, and A. Chehab, “Edge computing enabling the internet of things,” in Internet of Things (WF-IoT), 2015 IEEE 2nd World Forum on. IEEE, 2015, pp. 603–608.
(11) 5Gppp, “5G Vision,” https://5g-ppp.eu/: February 2015.
(12) M. Chen, Y. Zhang, L. Hu, T. Taleb, and Z. Sheng, “Cloud-based wireless network: Virtualized, reconfigurable, smart wireless network to enable 5g technologies,” Mobile Networks and Applications, vol. 20, no. 6, pp. 704–712, 2015.
(13) G. Klas, “ETSI MEC Use Cases and Requirements,” http://www.etsi.org/: October 2016.
(14) N. Sprecher, “Mobile Edge Computing An enabler for enhanced Car2X communication,” http://www.etsi.org/: June 2016.
(15) S. Fili, M. Paolini, “Power at the edge processing and storage move from the central core to the network edge,” : White paper, February 2017.
(16) Abourezq, M., Idrissi, A. Introduction of an outranking method in the Cloud computing research and Selection System based on the Skyline. Proceedings - International Conference on Research Challenges in Information Science. 2014.
(17) Idrissi, A. Some methods to treat capacity allocation problems. Journal of Theoretical and Applied Information Technology. 2012.
(18) Idrissi, A., Abourezq, M. Skyline in cloud computing. Journal of Theoretical and Applied Information Technology. 2014.
(19) Abourezq, M., Idrissi, A. A cloud services research and selection system. Proceedings of International Conference on Multimedia Computing and Systems. 2014.
(20) Yakine, F., Idrissi, A. Energy-aware topology control and QoS routing in ad-hoc networks. Procedia Computer Science. 2015.
(21) Idrissi, A., Rehioui, H., Laghrissi, A., Retal, S. An improvement of DENCLUE algorithm for the data clustering. 5th International Conference on Information and Communication Technology and Accessibility, ICTA 2015. 2015.
(22) Rehioui, H., Idrissi, A., Abourezq, M., Zegrari, F. DENCLUE-IM: A New Approach for Big Data Clustering. Procedia Computer Science. 2016.
(23) Idrissi, A., Yakine, F. Multicast routing with quality of service constraints in the ad hoc wireless networks. Journal of Computer Science. 2014.