Deep Learning for Edge Computing Applications: A Comprehensive Survey
DOI:
https://doi.org/10.51983/ajcst-2022.11.2.3456Keywords:
Security, IoT, Federated Learning, Edge Server, Edge ComputingAbstract
Edge computing is a modern computer architecture that processes data quickly and efficiently close to its point of origin, hence avoiding slowdowns caused by network latency and capacity limitations. By moving processing power to the network’s perimeter, edge computing decreases the load on central data centers and reduces the time it takes for users to submit data. Therefore, access latency may become a barrier, potentially negating the benefits of edge computing, particularly for applications that need a great deal of data.. Edge computing has some challenges, such as security, incomplete data, investment costs, and maintenance costs. In this research, we undertake a thorough analysis of edge computing, how edge device placement improves performance in IoT networks, compare various edge computing implementations, and explain various difficulties encountered during edge computing implementation. This study aims to promote creative edge-based Internet of Things security design by thoroughly examining existing Internet of Things security solutions at the edge layer and facilitate the dynamic deployment of edge devices.
References
N. Abbas, Y. Zhang, A. Taherkordi and T. Skeie, “Mobile Edge Computing: A Survey,” IEEE Internet of Things Journal, Vol. 5, No. 1, pp. 450-465, Feb. 2018, DOI: 10.1109/JIOT.2017.2750180.
Q. Luo, S. Hu, C. Li, G. Li and W. Shi, “Resource Scheduling in Edge Computing: A Survey,” IEEE Communications Surveys & Tutorials, Vol. 23, No. 4, pp. 2131-2165, Fourth quarter 2021, DOI: 10.1109/ COMST.2021.3106401.
M. Satyanarayanan, “The Emergence of Edge Computing,” Computer, Vol. 50, No. 1, pp. 30-39, Jan. 2017, DOI: 10.1109/MC.2017.9.
E. Ahmed et al., “Bringing Computation Closer toward the User Network: Is Edge Computing the Solution?,” IEEE Communications Magazine, Vol. 55, No. 11, pp. 138-144, Nov. 2017, DOI: 10.1109/MCOM.2017.1700120.
W. Khan, E. Ahmed, S. Hakak, I. Yaqoob and A. Ahmed, “Edge computing: A survey,” Future Generation Computer Systems, Vol. 97, pp. 219-235, Aug. 2019.
D. Kimovski, N. Mehran, C. E. Kerth and R. Prodan, “Mobility-Aware IoT Application Placement in the Cloud - Edge Continuum,” in IEEE Transactions on Services Computing, Vol. 15, No. 6, pp. 3358-3371, 1 Nov.-Dec. 2022, DOI: 10.1109/TSC.2021.3094322.
M. Nikravan and M.H. Kashani, “A review on trust management in fog/edge computing: Techniques, trends, and challenges,” Journal of Network and Computer Applications, Apr. 2022.
E. Gyamfi and A. Jurcut, “Intrusion Detection in Internet of Things Systems: A Review on Design Approaches Leveraging Multi-Access Edge Computing, Machine Learning, and Datasets,” Sensors, Vol. 22, No. 10, pp. 3744, May 2022, DOI: 10.3390/s22103744.
S. J. Stolfo, M. B. Salem and A. D. Keromytis, “Fog Computing: Mitigating Insider Data Theft Attacks in the Cloud,” 2012 IEEE Symposium on Security and Privacy Workshops, San Francisco, CA, USA, pp. 125-128, 2012, DOI: 10.1109/SPW.2012.19.
G. Kurikala, K. Gupta and A. Swapna, “Fog computing: Implementation of security and privacy to comprehensive approach for avoiding knowledge thieving attack exploitation decoy technology,” International Journal of Scientific Research in Computer Science, Engineering and Information Technology, Vol. 2, No. 4, pp. 176-181, Aug. 2017.
V. Mandlekar, V. Mahale, S. Sancheti and M. Rais, “Survey on fog computing mitigating data theft attacks in cloud,” International Journal of Innovative Research in Computer Science and Technology, Vol. 2, No. 6, pp. 13-16, 2014.
A. Filali, A. Abouaomar, S. Cherkaoui, A. Kobbane and M. Guizani, “Multi-Access Edge Computing: A Survey,” in IEEE Access, Vol. 8, pp. 197017-197046, 2020, DOI: 10.1109/ACCESS.2020.3034136.
P. Ranaweera, A. D. Jurcut and M. Liyanage, “Survey on Multi-Access Edge Computing Security and Privacy,” in IEEE Communications Surveys & Tutorials, Vol. 23, No. 2, pp. 1078-1124, Second quarter 2021, DOI: 10.1109/COMST.2021.3062546.
E. Ollora Zaballa, D. Franco, M. Aguado and M. S. Berger, “Next-generation SDN and fog computing: a new paradigm for SDN-based edge computing,” In2nd Workshop on Fog Computing and the IoT (Fog-IoT 2020) 2020.
A. Yousefpour, C. Fung, T. Nguyen, K. Kadiyala, F. Jalali, A. Niakanlahiji, J. Kong and J. P. Jue, “All one needs to know about fog computing and related edge computing paradigms: A complete survey,” Journal of Systems Architecture, Vol. 98, No. 1, pp. 289-330, Sep 2019.
P. Verma, R. Tiwari, W. C. Hong, S. Upadhyay and Y. H. Yeh, “FETCH: A Deep Learning-Based Fog Computing and IoT Integrated Environment for Healthcare Monitoring and Diagnosis,” in IEEE Access, Vol. 10, pp. 12548-12563, 2022, DOI: 10.1109/ACCESS.20 22.3143793.
Q. Qi and F. Tao, “A Smart Manufacturing Service System Based on Edge Computing, Fog Computing, and Cloud Computing,” in IEEE Access, Vol. 7, pp. 86769-86777, 2019, DOI: 10.1109/ACCESS.2019.2923610.
A. Jain and P. Singhal, “Fog computing: Driving force behind the emergence of edge computing,” 2016 International Conference System Modeling & Advancement in Research Trends (SMART), Moradabad, India, pp. 294-297, 2016, DOI: 10.1109/SYSMART.2016.7894538.
Y. Ai, M. Peng and K. Zhang, “Edge computing technologies for Internet of Things: a primer,” Digital Communications and Networks, Vol. 4, No. 2, pp. 77-86, Apr. 2018.
A. M. Alwakeel, “An Overview of Fog Computing and Edge Computing Security and Privacy Issues,” Sensors, Vol. 21, No. 24, pp. 8226, Dec. 2021, DOI: 10.3390/s21248226.
Y. Zhao, W. Wang, Y. Li, C. Colman Meixner, M. Tornatore and J. Zhang, “Edge Computing and Networking: A Survey on Infrastructures and Applications,” in IEEE Access, Vol. 7, pp. 101213-101230, 2019, DOI: 10.1109/ACCESS.2019.2927538.
S. J. Bigelow, “What is edge computing? Everything you need to know,” 2021.
G. Cui et al., “Efficient Verification of Edge Data Integrity in Edge Computing Environment,” in IEEE Transactions on Services Computing, Vol. 15, No. 6, pp. 3233-3244, 1 Nov.-Dec. 2022, DOI: 10.1109/TSC.2021.3090173.
J. Ren, D. Zhang, S. He, Y. Zhang and T. Li, “A survey on end-edge-cloud orchestrated network computing paradigms: Transparent computing, mobile edge computing, fog computing, and cloudlet,” ACM Computing Surveys (CSUR), Vol. 52, No. 6, pp. 1-36, Oct. 2019.
S. Yang, F. Li, M. Shen, X. Chen, X. Fu and Y. Wang, “Cloudlet Placement and Task Allocation in Mobile Edge Computing,” in IEEE Internet of Things Journal, Vol. 6, No. 3, pp. 5853-5863, June 2019, DOI: 10.1109/JIOT.2019.2907605.
A. T. Atieh, “The Next Generation Cloud technologies: A Review On Distributed Cloud, Fog And Edge Computing and Their Opportunities and Challenges”, RRST, Vol. 1, No. 1, pp. 1-15, Oct. 2021.
M. Liyanage, P. Porambage, A. Y. Ding and A. Kalla, “Driving forces for multi-access edge computing (MEC) IoT integration in 5G,” ICT Express, Vol. 7, No. 2, pp. 127-137, June 2021.
W. Xu, Z. Yang, D.W. Ng, M. Levorato and Y. C. Eldar, “Edge Learning for B5G Networks with Distributed Signal Processing: Semantic Communication, Edge Computing, and Wireless Sensing,” arXiv preprint arXiv:2206.00422, June 2022.
Y. Dai and Y. Zhang, “Adaptive Digital Twin for Vehicular Edge Computing and Networks,” in Journal of Communications and Information Networks, Vol. 7, No. 1, pp. 48-59, March 2022, DOI: 10.23919/JCIN.2022.9745481.
H. G. Abreha, M. Hayajneh, and M. A. Serhani, “Federated Learning in Edge Computing: A Systematic Survey,” Sensors, Vol. 22, No. 2, pp. 450, Jan. 2022, DOI: 10.3390/s22020450.
L. Liu, L. Chen, S. Xu, Y. Xu and C. Shi, “Design and implementation of intelligent monitoring terminal for distribution room based on edge computing,” Energy Reports, Vol. 7, No. 1, pp. 1131-1138, Nov. 2021.
S. Lee, L. Ayton, F. Bertagnolio, S. Moreau, T. P. Chong and P. Joseph. “Turbulent boundary layer trailing-edge noise: Theory, computation, experiment, and application,” Progress in Aerospace Sciences, Vol. 126, No. 1, Oct. 2021.
Y. Kalyani and R. Collier, “A Systematic Survey on the Role of Cloud, Fog, and Edge Computing Combination in Smart Agriculture,” Sensors, Vol. 21, No. 17, pp. 5922, Sep. 2021, DOI: 10.3390/s21175 922.
R. Anusuya, D. K. Renuka and L. A. Kumar, “Review on Challenges of Secure Data Analytics in Edge Computing,” in 2021 International Conference on Computer Communication and Informatics (ICCCI), Coimbatore, India, 2021, pp. 1-5, DOI: 10.1109/ICCCI50826.2021.9402559.
D. Mishra, D. Dharminder, P. Yadav, Y. S. Rao, P. Vijayakumar and N. Kumar, “A provably secure dynamic ID-based authenticated key agreement framework for mobile edge computing without a trusted party,” Journal of Information Security and Applications, Vol. 55, No. 1, Dec. 2020.
Z. Zhang et al., “Cloud Computing Placement Optimization Under Ubiquitous Power Internet of Things Background,” 2019 IEEE International Conference on Smart Cloud (SmartCloud), Tokyo, Japan, 2019, pp. 13-18, DOI: 10.1109/SmartCloud.2019.00012.
Y. Liang and T. Li, “Ubiquitous Power Internet of Things-Oriented Low-Latency Edge Task Scheduling Optimization Strategy,” Frontiers in Energy Research, Vol. 94, No. 10, pp. 72-98, June 2022.
L. Cao, Z. Wang and Y. Yue, “Analysis and prospect of the application of wireless sensor networks in ubiquitous power internet of things,” Computational Intelligence and Neuroscience, June 2022.
A. Singh, S. C. Satapathy, A. Roy and A. Gutub, “Ai-based mobile edge computing for IOT: Applications, challenges, and future scope,” Arabian Journal for Science and Engineering, Vol. 3, No. 1, pp. 1-31, Jan. 2022.
J. Li, W. Liang, W. Xu, Z. Xu, Y. Li and X. Jia, “Service Home Identification of Multiple-Source IoT Applications in Edge Computing,” in IEEE Transactions on Services Computing, DOI: 10.1109/TSC.2022.3176576.
P. Porambage, J. Okwuibe, M. Liyanage, M. Ylianttila and T. Taleb, “Survey on Multi-Access Edge Computing for Internet of Things Realization,” in IEEE Communications Surveys & Tutorials, Vol. 20, No. 4, pp. 2961-2991, Fourth quarter 2018, DOI: 10.1109/COMST. 2018.2849509.
Z. Li, W. M. Wang, G. Liu, L. Liu, J. He, G. Q. Huang, “Toward open manufacturing: A cross-enterprises knowledge and services exchange framework based on blockchain and edge computing,” Industrial Management & Data Systems, Feb. 2018.
L. H. Phuc, L. A. Phan and T. Kim, “Traffic-Aware Horizontal Pod Autoscaler in Kubernetes-Based Edge Computing Infrastructure,” in IEEE Access, Vol. 10, pp. 18966-18977, 2022, DOI: 10.1109/ ACCESS.2022.3150867.
K. Sha, T. A. Yang, W. Wei and S. Davari, “A survey of edge computing-based designs for IoT security,” Digital Communications and Networks. Vol. 6, No. 2, pp. 195-202, May. 2020.
M. Goudarzi, H. Wu, M. Palaniswami and R. Buyya, “An Application Placement Technique for Concurrent IoT Applications in Edge and Fog Computing Environments,” in IEEE Transactions on Mobile Computing, Vol. 20, No. 4, pp. 1298-1311, 1 April 2021, DOI: 10.1109/TMC.2020.2967041.
K. Cao, Y. Liu, G. Meng and Q. Sun, “An Overview on Edge Computing Research,” in IEEE Access, Vol. 8, pp. 85714-85728, 2020, DOI: 10.1109/ACCESS.2020.2991734.
S. Mondal, G. Das and E. Wong, “Cost-optimal cloudlet placement frameworks over fiber-wireless access networks for low-latency applications,” Journal of Network and Computer Applications, Vol. 138, pp. 27-38, July 2022.
C. Li, Y. Wang, H. Tang, Y. Zhang, Y. Xin and Y. Luo, “Flexible replica placement for enhancing the availability in edge computing environment,” Computer Communications, Vol. 146, pp. 1-4, Oct. 2019.
