Advertisement

Partial Offloading for Fog Computing Using P2P Based File-Sharing Protocol

  • Satanu Maity
  • Sujoy Mistry
Conference paper
  • 6 Downloads
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1119)

Abstract

In the world of Internet of Things (IoT), promising paradigm such as fog computing has been emerged as an extension of cloud computing infrastructure to provide low latency and better QoS to the end-user specifically for time-sensitive applications. One of the major challenges of these applications is the task offloading, where resource-constraint end-user devices migrate the tasks to the nearby resource-rich computing environment for execution. There are several factors like latency optimization, resource management that need to be addressed for performing the task offloading. In this work, we aim to provide a new offloading technique where latency for task offloading has been optimized by taking Peer-to-Peer (P2P) technology as a basic mode of a network environment for fog computing and also taken P2P file-sharing protocol as a basic mode of offloading technique.

Keywords

Fog computing Task offloading Delay minimization Peer-to-Peer file-sharing protocol 

References

  1. 1.
    Kumar, A., Ranjan, A., Gangwar, U.: An understanding approach towards cloud computing. Int. J. Emerging Technol. Adv. Eng. 2(9) (2012)Google Scholar
  2. 2.
    Dillon, T.S., Wu, C., Chang, E.: Cloud computing: issues and challenges. In: 2010 24th IEEE International Conference on Advanced Information Networking and Applications, pp. 27–33 (2010)Google Scholar
  3. 3.
    Mishra, B.S.P., Das, H., Dehuri, S., Jagadev, A.K.: Cloud Computing for Optimization: Foundations, Applications, and Challenges, vol. 39. Springer, Berlin (2018)Google Scholar
  4. 4.
    Jalali, F., Hinton, K., Ayre, R., Alpcan, T., Tucker, R.: Fog computing may help to save energy in cloud computing. IEEE J. Sel. Areas Commun. 34, 1728–1739 (2016)CrossRefGoogle Scholar
  5. 5.
    Hu, P., Dhelim, S., Ning, H., Qiu, T.: Survey on fog computing: architecture, key technologies, applications and open issues. J. Netw. Comput. Appl. 98, 27–42 (2017)CrossRefGoogle Scholar
  6. 6.
    Mahmud, R., Buyya, R.: Fog Computing: A Taxonomy, Survey and Future Directions (2018). https://arxiv.org/abs/1611.05539
  7. 7.
    Bozorgchenani, A., Tarchi, D., Corazza, G.E.: An energy and delay-efficient partial offloading technique for fog computing architectures. In: GLOBECOM 2017–2017 IEEE Global Communications Conference, pp. 1–6 (2017)Google Scholar
  8. 8.
    Bozorgchenani, A., Tarchi, D., Corazza, G.E.: Centralized and distributed architectures for energy and delay efficient fog network-based edge computing services. IEEE Trans. Green Commun. Netw. 3, 250–263 (2019)CrossRefGoogle Scholar
  9. 9.
    Barik, R.K., Dubey, H., Mankodiya, K.: SOA-FOG: secure service-oriented edge computing architecture for smart health big data analytics. In: 2017 IEEE Global Conference on Signal and Information Processing (GlobalSIP), pp. 477–481 (2017)Google Scholar
  10. 10.
    Chakrabarty, A., Heya, T., Hossain, M., Arefin, S., Joy, K.: A novel extended-cloud based approach for Internet of Things. In: Studies in Big Data, pp. 303–331 (2018)Google Scholar
  11. 11.
    Santos, J., Wauters, T., Volckaert, B., Turck, F.D.: Fog computing: enabling the management and orchestration of smart city applications in 5G networks. Entropy 20, 4 (2017)CrossRefGoogle Scholar
  12. 12.
    Gazzetti, M., Reale, A., Katrinis, K., Corradi, A.: Scalable linux container provisioning in fog and edge computing platforms. In: Euro-Par 2017: Parallel Processing Workshops, pp. 304–315 (2018)Google Scholar
  13. 13.
    Al-khafajiy, M., Baker, T., Waraich, A., Al-Jumeily, D., Hussain, A.: IoT-Fog Optimal Workload via Fog Offloading. In: 2018 IEEE/ACM International Conference on Utility and Cloud Computing Companion (UCC Companion) (2018)Google Scholar
  14. 14.
    Saqib, M., Hamid, M.: FogR: A highly reliable and intelligent computation offloading on the Internet of Things. In: 2016 IEEE Region 10 Conference (TENCON) (2016)Google Scholar
  15. 15.
    Kui, X., Sun, Y., Zhang, S., Li, Y.: Characterizing the capability of vehicular fog computing in large-scale urban environment. Mobile Netw. Appl. 23, 1050–1067 (2018)CrossRefGoogle Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  • Satanu Maity
    • 1
  • Sujoy Mistry
    • 1
  1. 1.Department of Computer Science and EngineeringMaulana Abul Kalam Azad University of TechnologyKolkataIndia

Personalised recommendations