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Journal of Artificial Intelligence and Metaheuristics
Volume 2 , Issue 2, PP: 18-28 , 2022 | Cite this article as | XML | Html |PDF

Title

Literature Review and Novel Trends of Mobile Edge Computing for 5G and Beyond

  Germien G. Sedhom 1 * ,   Alshimaa H. Ismail 2 ,   Basma M. Yousef 3

1  Department of Communications and Electronics Engineering, Delta Higher Institute for Engineering and Technology, Talkha 35111, Egypt.
    (germien_ggs@yahoo.com)

2  Department of Communications and Electronics Engineering, Delta Higher Institute for Engineering and Technology, Talkha 35111, Egypt.
    (eng.alshimaahamdy@gmail.com)

3  Department of Communications and Electronics Engineering, Delta Higher Institute for Engineering and Technology, Talkha 35111, Egypt.
    (basmamyousef@gmail.com)


Doi   :   https://doi.org/10.54216/JAIM.020202

Received: May 21, 2022 Accepted: November 11, 2022

Abstract :

Because of the rapid evolution of communications technologies, such as the Internet of Things (IoT) and fifth generation (5G) systems and beyond, the latest developments have seen a fundamental change in mobile computing. Mobile computing is moved from central mobile cloud computing to mobile edge computing (MEC). Therefore, MEC is considered an essential technology for 5G technology and beyond. The MEC technology permits user equipment (UEs) to execute numerous high-computational operations by creating computing capabilities at the edge networks and inside access networks. Consequently, in this paper, we extensively address the role of MEC in 5G networks and beyond. Accordingly, we first investigate the MEC architecture, the characteristics of edge computing, and the MEC challenges. Then, the paper discusses the MEC use cases and service scenarios. Further, computations offloading is explored. Lastly, we propose upcoming research difficulties in incorporating MEC with the 5G system and beyond.

Keywords :

Mobile edge computing; 5G; Computation Offloading. 

References :

[1]  Yousefpour, A., Fung, C., Nguyen, T., Kadiyala, K., Jalali, F., Niakanlahiji, A., … & Jue, J. P., 

All one needs to know about fog computing and related edge computing paradigms: A complete 

survey. Journal of Systems Architecture, 98, 289-330, 2019. 

[2]  Kimovski, D., Mathá, R., Hammer, J., Mehran, N., Hellwagner, H., & Prodan, R., Cloud, fog, or 

edge: Where to compute. IEEE Internet Computing, 25(4), 30-36, 2021. 

[3]  Dinh, H. T., Lee, C., Niyato, D., & Wang, P., A survey of mobile cloud computing: architecture, 

applications, and approaches. Wireless communications and mobile computing, 13(18), 15871611, 

2013. 

[4]  Pham, Q. V., Fang, F., Ha, V. N., Piran, M. J., Le, M., Le, L. B., ... & Ding, Z., A survey of 

multiaccess edge computing in 5G and beyond: Fundamentals, technology integration, and stateof-theart. IEEE Access, 8, 116974-117017, 2020. 

[5]  Mao, Y., You, C., Zhang, J., Huang, K., & Letaief, K. B., A survey on mobile edge computing: 

The communication perspective.  IEEE communications surveys & tutorials, 19(4), 2322-2358, 

2017. 

[6]  Khan, W. Z., Ahmed, E., Hakak, S., Yaqoob, I., & Ahmed, A., Edge computing: A survey. Future 

Generation Computer Systems, 97, 219-235, 2019. 

[7]  Peng,  K.,  Leung,  V.,  Xu,  X.,  Zheng,  L.,  Wang,  J.,  &  Huang,  Q.,  A  survey  on  mobile  edge 

computing: Focusing on service adoption and provision.  Wireless Communications and Mobile 

Computing, 2018. 

[8]  Kekki, S., Featherstone, W., Fang, Y., Kuure, P., Li, A., Ranjan, A., ... & Scarpina, S. (2018). 

MEC in 5G networks. ETSI white paper, 28(28), 1-28, 2018. 

[9]  Mach,  P.,  &  Becvar,  Z.,  Mobile  edge  computing:  A  survey  on  architecture  and  computation 

offloading. IEEE communications surveys & tutorials, 19(3), 1628-1656, 2017. 

[10]  Ismail, A. H., El-Bahnasawy, N. A., & Hamed, H. F., AGCM: Active Queue Management-Based

Green Cloud Model for Mobile Edge Computing. Wireless Personal Communications, 104(4), 1-21, 2019. 

[11]  Li, H., Shou, G., Hu, Y., & Guo, Z., Mobile edge computing: Progress and challenges. In 2016 4th 

IEEE  international  conference  on  mobile  cloud  computing,  services,  and  engineering  (Mobile 

Cloud), 83-84, 2016. 

[12]  Abbas,  N.,  Zhang,  Y.,  Taherkordi,  A.,  &  Skeie,  T.,  Mobile  edge  computing:  A  survey.  IEEE 

Internet of Things Journal, 5(1), 450-465, 2017. 

[13]  Hu, Y. C., Patel, M., Sabella, D., Sprecher, N., & Young, V., Mobile edge computing: A key 

technology towards 5G. ETSI white paper, 11(11), 1-16, 2015. 

[14]  Qadir, J., Sainz-De-Abajo, B., Khan, A., Garcia-Zapirain, B., De La Torre-Diez, I., & Mahmood, 

H., Towards mobile edge computing: Taxonomy, challenges, applications and future realms. IEEE 

Access, 8, 189129-189162, 2020. 

[15]  Mao, Y., Zhang, J., & Letaief, K. B., Dynamic computation offloading for mobile-edge computing 

with  energy  harvesting  devices.  IEEE  Journal  on  Selected  Areas  in  Communications,  34(12), 

3590-3605, 2016. 

[16]  Oueis,  J.,  Strinati,  E.  C.,  & Barbarossa,  S.,  Distributed  mobile  cloud  computing:  A  multi-user 

clustering solution. In 2016 IEEE International Conference on Communications (ICC), 1-6, 2016. 

[17]  Zhang, K., Mao, Y., Leng, S., Vinel, A., & Zhang, Y., Delay constrained offloading for mobile 

edge  computing  in  cloud-enabled  vehicular  networks.  In  2016  8th  International  Workshop  on 

Resilient Networks Design and Modeling (RNDM), 288-294, 2016. 

[18]  Zhan, W., Luo, C., Min, G., Wang, C., Zhu, Q., & Duan, H., Mobility-aware multi-user offloading 

optimization  for  mobile  edge  computing.  IEEE  Transactions  on  Vehicular  Technology,  69(3), 

3341-3356, 2020. 

[19]  Saleem, U., Liu, Y., Jangsher, S., Tao, X., & Li, Y., Latency minimization for D2D-enabled partial 

computation offloading in mobile edge computing.  IEEE Transactions on Vehicular Technology, 

69(4), 4472-4486, 2020. 

[20]  Lieira, D. D., Quessada, M. S., Cristiani, A. L., & Meneguette, R. I., Algorithm for 5G resource 

management  optimization  in  edge  computing.  IEEE  Latin  America  Transactions,  19(10), 

17721780., 2021. 

[21]  Zhou, F., & Hu, R. Q., Computation efficiency maximization in wireless-powered mobile edge 

computing networks. IEEE Transactions on Wireless Communications, 19(5), 3170-3184, 2020. 

[22]  Wang,  X.,  Han,  Y.,  Leung,  V.  C.,  Niyato,  D.,  Yan,  X.,  &  Chen,  X.,  Convergence  of  edge 

computing  and  deep  learning:  A  comprehensive  survey.  IEEE  Communications  Surveys  & 

Tutorials, 22(2), 869-904, 2020. 

[23]  Wang, F., Xu, J., & Cui, S., Optimal energy allocation and task offloading policy for wireless 

powered mobile edge computing systems. IEEE Transactions on Wireless 

Communications, 19(4), 2443-2459, 2020. 

[24]  Tomaszewski, L., Kukliński, S., & Kołakowski, R., A new approach to 5G and MEC integration. 

In  IFIP  International  Conference  on  Artificial  Intelligence  Applications  and  Innovations , 

Springer, Cham, 15-24, 2020. 

[25]  Barakabitze, A. A., Ahmad, A., Mijumbi, R., & Hines, A., 5G network slicing using SDN and 

NFV:  A  survey  of  taxonomy,  architectures  and  future  challenges.  Computer  Networks,  167, 

106984, 2020.  

[26]  Abd-Elnaby, M., Sedhom, G. G., El-Rabaie, E. S. M., & Elwekeil, M., NOMA for 5G and beyond: 

literature review and novel trends. Wireless Networks, 1-25, 2022. 

[27]  Kiani, A., & Ansari, N., Edge computing aware NOMA for 5G networks. IEEE Internet of Things 

Journal, 5(2), 1299-1306, 2018. 

[28]  Du, J., Liu, W., Lu, G., Jiang, J., Zhai, D., Yu, F. R.,  & Ding, Z., When mobile-edge computing 

(MEC) meets nonorthogonal multiple access (NOMA) for the Internet of Things (IoT): System 

design and optimization. IEEE Internet of Things Journal, 8(10), 7849-7862, 2020. 

[29]  Pan,  Y.,  Chen,  M.,  Yang, Z.,  Huang,  N.,  &  Shikh-Bahaei,  M.,  Energy-efficient  NOMA-based 

mobile edge computing offloading. IEEE Communications Letters, 23(2), 310-313, 2018. 

[30]  Mohajer,  A.,  Daliri,  M.  S.,  Mirzaei,  A.,  Ziaeddini,  A.,  Nabipour,  M.,  &  Bavaghar,  M., 

Heterogeneous  computational  resource  allocation  for  NOMA:  Toward  green  mobile 

edgecomputing systems. IEEE Transactions on Services Computing, 2022. 

[31]  Meng, A., Wei, G., Zhao, Y., Gao, X., & Yang, Z., Green resource allocation for mobile edge 

computing. Digital Communications and Networks, 2022. 

[32]  Liu, J., & Liu, X., Energy-efficient allocation for multiple tasks in mobile edge computing. Journal 

of Cloud Computing, 11(1), 1-14, 2022. 

[33]  Li,  Y.,  Xu,  G.,  Ge,  J.,  Liu,  P.,  &  Fu,  X.,  Energy-efficient  resource  allocation  for  application 

including  dependent  tasks  in  mobile  edge  computing.  KSII  Transactions  on  Internet  and 

Information Systems (TIIS), 14(6), 2422-2443, 2020. 

[34]  Bahreini, T., Badri,  H., & Grosu, D., Mechanisms for resource allocation and pricing in mobile 

edge computing systems. IEEE Transactions on Parallel and Distributed Systems, 33(3), 667-682, 

2021. 

[35]  Zhou,  Y.,  Yu,  F.  R.,  Chen,  J.,  &  He,  B.,  Joint  Resource  Allocation  for  Ultra-Reliable  and 

LowLatency  Radio  Access  Networks  with  Edge  Computing.  IEEE  Transactions  on  Wireless 

Communications, 21(1), 444-460, 2021. 

[36]  Chen,  X.,  Cai,  Y.,  Li,  L.,  Zhao,  M.,  Champagne,  B.,  &  Hanzo,  L.,  Energy-efficient  resource 

allocation  for  latency-sensitive  mobile  edge  computing.  IEEE  Transactions  on  Vehicular 

Technology, 69(2), 2246-2262, 2019. 

[37]  Salama,  G.  M.,  Ismail,  A.  H.,  Soliman,  T.  A.,  Hamed,  H.  F.,  &  El‐Bahnasawy,  N.  A., 

Congestionaware multiaccess edge computing collaboration model for 5G. International Journal 

of Communication Systems, 33(12), e4446, 2020. 

[38]  Dong,  X.,  Li,  X.,  Yue,  X.,  &  Xiang,  W.,  Performance  analysis  of  cooperative  NOMA  based 

intelligent mobile edge computing system. China Communications, 17(8), 45-57, 2020. 

[39]  Li, B., Si, F., Zhao, W., & Zhang, H., Wireless powered mobile edge computing with NOMA and 

user cooperation. IEEE Transactions on Vehicular Technology, 70(2), 1957-1961, 2021. 

[40]  Ren, M., Chen, J., He, B., Wu, K., Zhou, Y., Xue, X., & Yang, L., Cooperative NOMA-MEC with 

Helper Scheduling. IEEE Communications Letters, 2022. 

[41]  Yılmaz, S. S., & Özbek, B., Multi-helper NOMA for cooperative mobile edge computing.  IEEE 

Transactions on Intelligent Transportation Systems, 23(7), 9819-9828, 2021. 

[42]  Zhao,  C.,  Cai,  Y.,  Liu,  A.,  Zhao,  M.,  &  Hanzo,  L.,  Mobile  edge  computing  meets  mm-Wave 

communications: Joint beamforming and resource allocation for system delay minimization. IEEE 

Transactions on Wireless Communications, 19(4), 2382-2396, 2020. 

[43]  Fang, F., Wu, B., Fu, S., Ding, Z., & Wang, X., Energy-Efficient Design of STAR-RIS Aided 

MIMO-NOMA Networks. IEEE Transactions on Communications, 2022. 

[44]  Michailidis, E. T., Miridakis, N. I., Michalas, A., Skondras, E., Vergados, D. J., & Vergados, D. 

D., Energy Optimization in Massive MIMO UAV-Aided MEC-Enabled Vehicular 

Networks. IEEE Access, 9, 117388-117403, 2021. 

[45]  Zeng, M., Hao, W., Dobre, O. A., & Poor, H. V., Delay minimization for massive MIMO assisted 

mobile edge computing. IEEE Transactions on Vehicular Technology, 69(6), 6788-6792, 2020. 

[46]  Cao, X., Liu, C., & Peng, M., Energy-efficient mobile edge computing in NOMA-based wireless 

networks:  A  game  theory  approach.  In  ICC  2020-2020  IEEE  International  Conference  on 

Communications (ICC), 1-6, 2020.  

[47]  Xu,  C.,  Zheng,  G.,  &  Tang, L.,  Energy-aware  user  association  for  NOMA-based  mobile  edge 

computing using matching-coalition game. IEEE Access, 61943-61955, 2020.  


Cite this Article as :
Style #
MLA Germien G. Sedhom, Alshimaa H. Ismail, Basma M. Yousef. "Literature Review and Novel Trends of Mobile Edge Computing for 5G and Beyond." Journal of Artificial Intelligence and Metaheuristics, Vol. 2, No. 2, 2022 ,PP. 18-28 (Doi   :  https://doi.org/10.54216/JAIM.020202)
APA Germien G. Sedhom, Alshimaa H. Ismail, Basma M. Yousef. (2022). Literature Review and Novel Trends of Mobile Edge Computing for 5G and Beyond. Journal of Journal of Artificial Intelligence and Metaheuristics, 2 ( 2 ), 18-28 (Doi   :  https://doi.org/10.54216/JAIM.020202)
Chicago Germien G. Sedhom, Alshimaa H. Ismail, Basma M. Yousef. "Literature Review and Novel Trends of Mobile Edge Computing for 5G and Beyond." Journal of Journal of Artificial Intelligence and Metaheuristics, 2 no. 2 (2022): 18-28 (Doi   :  https://doi.org/10.54216/JAIM.020202)
Harvard Germien G. Sedhom, Alshimaa H. Ismail, Basma M. Yousef. (2022). Literature Review and Novel Trends of Mobile Edge Computing for 5G and Beyond. Journal of Journal of Artificial Intelligence and Metaheuristics, 2 ( 2 ), 18-28 (Doi   :  https://doi.org/10.54216/JAIM.020202)
Vancouver Germien G. Sedhom, Alshimaa H. Ismail, Basma M. Yousef. Literature Review and Novel Trends of Mobile Edge Computing for 5G and Beyond. Journal of Journal of Artificial Intelligence and Metaheuristics, (2022); 2 ( 2 ): 18-28 (Doi   :  https://doi.org/10.54216/JAIM.020202)
IEEE Germien G. Sedhom, Alshimaa H. Ismail, Basma M. Yousef, Literature Review and Novel Trends of Mobile Edge Computing for 5G and Beyond, Journal of Journal of Artificial Intelligence and Metaheuristics, Vol. 2 , No. 2 , (2022) : 18-28 (Doi   :  https://doi.org/10.54216/JAIM.020202)