International Journal of Distributed and Cloud Computing

Open Access Open Access  Restricted Access Subscription Access
Open Access Open Access Open Access  Restricted Access Restricted Access Subscription Access

Comparative Study of Cloud Computing and Edge Computing: Three Level Architecture Models and Security Challenges


Affiliations
1 Student, Department of Computer Science & Engineering, Vivekananda Institute of Technology, Jaipur, Rajasthan, India
2 Independent Researcher, Jaipur, Rajasthan, India
     

   Subscribe/Renew Journal


The procreation of IoT (Internet of Things), mobile internet and the attainment of cloud computing services have innovated a new computing archetype, known as edge computing. According to the International Data Corporation (IDC) forecast, worldwide data will reach about 180 zettabytes (ZB) and out of which 70% of data generated by IoT devices will be processed on the edge of the network by 2025. IDC also forecasts the IoT devices connected to reach 150 billion by 2025. Edge computing has the ability to deal with the huge volume of data and to handle the requirement of response time, data handling, bandwidth cost saving, along with privacy and data security. Edge computing enables low latency, mobility, and real-time data processing at a very faster pace. This paper is meant to introduce with the notion of edge computing, the three-level architecture of the edge model with the detailed difference between the edge computing model and the traditional cloud model. The various edge models that enable processing at the edge includes mobile edge computing, fog computing and cloudlet computing. Possessing the various advantages and models, edge computing still suffers from various security challenges. The paper concludes stating the security challenges that edge computing still need to focus upon.

Keywords

Cloud architecture, Cloud computing, Edge computing, IoT
Subscription Login to verify subscription
User
Notifications
Font Size


  • W. Shi, G. Pallis, and Z. Xu, “Edge computing” Proceedings of the IEEE, vol. 107, no. 8, pp. 1474-1481, Aug. 2019.

  • V. Gezer, J. Um, and M. Ruskowski, “An introduction to edge computing and a real-time capable server architecture,” International Journal on Advances in Intelligent Systems, vol. 11, no. 1&2, pp. 105-113, 2018.

  • S. B. Calo, M. Touna, D. C. Verma, and A. Cullen, “Edge computing architecture for applying AI to IoT,” 2017 IEEE International Conference on Big Data (Big Data), Boston, MA, 2017, pp. 3012-3016, doi: 10.1109/ BigData.2017.8258272.

  • M. De Donno, K. Tange, and N. Dragoni, “Foundations and evolution of modern computing paradigms: Cloud, IoT, edge, and fog,” IEEE Access, vol. 7, pp. 150936150948, 2019, doi: 10.1109/ACCESS.2019.2947652.

  • S. Singh, “Optimize cloud computations using edge computing,” 2017 International Conference on Big Data, IoT and Data Science (BID), Pune, India, 2017, pp. 49-53, doi:10.1109/BID.2017.8336572.

  • K. Dolui, and S. K. Datta, “Comparison of edge computing implementations: Fog computing, cloudlet and mobile edge computing,” 2017 Global Internet of Things Summit (GIoTS), Geneva, Switzerland, 2017, pp.1-6, doi: 10.1109/GIOTS.2017.8016213.

  • S. Fayaz, and U. I. Wani, “Introduction to the edge computing architecture” Journal of Emerging Technologies and Innovative Research (JETIR), vol. 5, no. 11, pp. 310-313, Nov. 2018.

  • C. M. Fernández, M. D. Rodríguez, and B. R. Muñoz, “An edge computing architecture in the internet of things,” 2018 IEEE 21st International Symposium on Real-Time Distributed Computing (ISORC), Singapore, 2018, pp. 99-102, doi: 10.1109/ISORC.2018.00021.

  • K. Dolui, and S. K. Datta, “Comparison of edge computing implementations: Fog computing, cloudlet and mobile edge computing,” 2017 Global Internet of Things Summit (GIoTS), Geneva, 2017, pp. 1-6, doi: 10.1109/GIOTS.2017.8016213.

  • B. P. Rimal, D. P. Van, and M. Maier, “Mobile-edge computing vs. centralized cloud computing in fiberwireless access networks,” 2016 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS), San Francisco, CA, 2016, pp. 991-996, doi: 10.1109/INFCOMW.2016.7562226.

  • S. Khanagha, S.(S.) Ansari, S. Paroutis, and L. Oviedo, “Mutualism and the dynamics of new platform creation: A study of Cisco and fog computing,” Strategic Management Journal, pp. 1-31, 2020. [Online].Available: https://doi.org/10.1002/smj.3147

  • S. Yi, Z. Hao, Z. Qin, and Q. Li, “Fog computing: Platform and applications,” 2015 Third IEEE Workshop on Hot Topics in Web Systems and Technologies (HotWeb), Washington, DC, 2015, pp. 73-78, doi: 10.1109/HotWeb.2015.22.

  • X. Sun, and N. Ansari, “EdgeIoT: Mobile edge computing for the internet of things,” IEEE Communications Magazine, vol. 54, no. 12, pp. 22-29, Dec. 2016, doi: 10.1109/MCOM.2016.1600492CM.

  • K. Dolui, and S. K. Datta, “Comparison of edge computing implementations: Fog computing, cloudlet and mobile edge computing,” 2017 Global Internet of Things Summit (GIoTS), Geneva, Switzerland, 2017, pp.1-6, doi: 10.1109/GIOTS.2017.8016213.

  • P. Tedeschi, and S. Sciancalepore, “Edge and fog computing in critical infrastructures: Analysis, security threats, and research challenges,” 2019 IEEE European Symposium on Security and Privacy Workshops (EuroS&PW), Stockholm, Sweden, 2019, pp. 1-10, doi:10.1109/EuroSPW.2019.00007.

  • J. Zhang, B. Chen, Y. Zhao, X. Cheng, and F. Hu,“Data security and privacy-preserving in edge computing paradigm: Survey and open issues,” IEEE Access, vol. 6, pp. 18209-18237, 2018, doi: 10.1109/ ACCESS.2018.2820162.

  • M. Satyanarayanan, “The emergence of edge computing,” Computer, vol. 50, no. 1, pp. 30-39, Jan.2017, doi: 10.1109/MC.2017.9.

  • I. Foster, Y. Zhao, I. Raicu, and S. Lu, “Cloud computing and grid computing 360-degree compared,” 2008 Grid Computing Environments Workshop, Austin, TX, 2008,pp. 1-10, doi: 10.1109/GCE.2008.4738445.


Abstract Views: 323

PDF Views: 0




  • Comparative Study of Cloud Computing and Edge Computing: Three Level Architecture Models and Security Challenges

Abstract Views: 323  |  PDF Views: 0

Authors

Abhay Verma
Student, Department of Computer Science & Engineering, Vivekananda Institute of Technology, Jaipur, Rajasthan, India
Vinay Verma
Independent Researcher, Jaipur, Rajasthan, India

Abstract


The procreation of IoT (Internet of Things), mobile internet and the attainment of cloud computing services have innovated a new computing archetype, known as edge computing. According to the International Data Corporation (IDC) forecast, worldwide data will reach about 180 zettabytes (ZB) and out of which 70% of data generated by IoT devices will be processed on the edge of the network by 2025. IDC also forecasts the IoT devices connected to reach 150 billion by 2025. Edge computing has the ability to deal with the huge volume of data and to handle the requirement of response time, data handling, bandwidth cost saving, along with privacy and data security. Edge computing enables low latency, mobility, and real-time data processing at a very faster pace. This paper is meant to introduce with the notion of edge computing, the three-level architecture of the edge model with the detailed difference between the edge computing model and the traditional cloud model. The various edge models that enable processing at the edge includes mobile edge computing, fog computing and cloudlet computing. Possessing the various advantages and models, edge computing still suffers from various security challenges. The paper concludes stating the security challenges that edge computing still need to focus upon.

Keywords


Cloud architecture, Cloud computing, Edge computing, IoT

References