KSII Transactions on Internet and Information Systems (TIIS)

Korean Society for Internet Information (한국인터넷정보학회)
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Adaptive Deadline-aware Scheme (ADAS) for Data Migration between Cloud and Fog Layers

  • Received : 2017.10.16
  • Accepted : 2017.10.21
  • Published : 2018.03.31
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Abstract

The advent of Internet of Things (IoT) and the evident inadequacy of Cloud networks concerning management of numerous end nodes have brought about a shift of paradigm giving birth to Fog computing. Fog computing is an extension of Cloud computing that extends Cloud resources at the edge of the network, closer to the user. Cloud computing has become one of the essential needs of people over the Internet but with the emerging concept of IoT, traditional Clouds seem inadequate. IoT entails extremely low latency and for that, the Cloud servers that are distant and unknown to the user appear to be unsuitable. With the help of Fog computing, the Fog devices installed would be closer to the user that will provide an immediate storage for the frequently needed data. This paper discusses data migration between different storage types especially between Cloud devices and then presents a mechanism to migrate data between Cloud and Fog Layer. We call this mechanism Adaptive Deadline-Aware Scheme (ADAS) for Data migration between Cloud and Fog. We will demonstrate that we can access and process latency sensitive "hot" data through the proposed ADAS more efficiently than with a traditional Cloud setup.

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References

  1. Bonomi, F., Milito, R., Natarajan, P., & Zhu, J., "Fog computing: A platform for internet of things and analytics," Big Data and Internet of Things: A Roadmap for Smart Environments Springer, International Publishing, pp. 169-186, 2014.
  2. Khalid, A., & Shahbaz, M., "Cloud computing technology: services and opportunities," Pakistan Journal of Science, vol. 65, no. 3, pp. 348-351, 2013.
  3. Madsen, H., Burtschy, B., Albeanu, G., Popentiu-Vladicescu, F. L., "Reliability in the utility computing era: Towards reliable fog computing," in Proc. of 2013 20th International Conference on Systems, Signals and Image Processing (IWSSIP), IEEE, pp. 43-46, 2013.
  4. Hong, K., Lillethun, D., Ramachandran, U., Ottenwalder, B., Koldehofe, B., "Mobile fog: A programming model for large-scale applications on the internet of things," in Proc. of Proceedings of the second ACM SIGCOMM workshop on Mobile cloud computing ACM, pp. 15-20, 2013.
  5. Naranjo, Paola G. Vinueza, Mohammad Shojafar, Leticia Vaca-Cardenas, Claudia Canali, Riccardo Lancellotti, Enzo Baccarelli, "Big Data Over SmartGrid-A Fog Computing Perspective," in Proc. of SOFTCOM Workshop, pp. 1-6. 2016
  6. Weiss, A., "Computing in the clouds," Computing, 2007.
  7. Dillon, T., Wu, C., Chang, E., "Cloud computing: issues and challenges," in Proc. of 2010 24th IEEE international conference on advanced information networking and applications, pp. 27-33, 2010.
  8. Bonomi, F., Milito, R., Zhu, J., Addepalli, S., "Fog computing and its role in the internet of things," in Proc. of Proceedings of the first edition of the MCC workshop on Mobile cloud computing, ACM, pp. 13-16, 2012.
  9. Siemens, G., Long, P., "Penetrating the Fog: Analytics in Learning and Education," EDUCAUSE review, vol. 46, no. 5, 2011.
  10. Nemirovsky, M., Milito, R., & Yanuzzi, M., "Fog computing," in Proc. of Class Conference ICREA/BSC, vol. 24, 2012.
  11. Zhang, G., Chiu, L., Liu, L., "Adaptive data migration in multi-tiered storage based cloud environment," in Proc. of 2010 IEEE 3rd International Conference on Cloud Computing, IEEE, pp. 148-155, 2010.
  12. Naranjo, P. G. V., Shojafar, M., Abraham, A., Baccarelli, E., "A new Stable Election-based routing algorithm to preserve aliveness and energy in fog-supported wireless sensor networks," in Proc. of Systems, Man, and Cybernetics (SMC), 2016 IEEE International Conference on, IEEE, pp. 002413-002418, 2016.
  13. Firdhous, M., Ghazali, O., Hassan, S., "Fog computing: Will it be the future of cloud computing?" in Proc. of The Third International Conference on Informatics & Applications (ICIA2014), 2014.
  14. Peter, N., "FOG Computing and Its Real Time Applications."
  15. Stojmenovic, I., Wen, S., "The fog computing paradigm: Scenarios and security issues," in Proc. of Computer Science and Information Systems (FedCSIS), 2014 Federated Conference on, IEEE., pp. 1-8, 2014.
  16. Frohlich, B., Plate, J., "The cubic mouse: a new device for three-dimensional input," in Proc. of Proceedings of the SIGCHI conference on Human Factors in Computing Systems, ACM, pp. 526-531, 2000.
  17. Baccarelli, E., Naranjo, P. G. V., Shojafar, M., Scarpiniti, M., "Q*: Energy and delay-efficient dynamic queue management in TCP/IP virtualized data centers," Computer Communications, vol. 102, pp. 89-106, 2017. https://doi.org/10.1016/j.comcom.2016.12.010
  18. Varshney, U., "Pervasive healthcare and wireless health monitoring," Mobile Networks and Applications, vol. 12, no. 2-3, pp. 113-127, 2007. https://doi.org/10.1007/s11036-007-0017-1
  19. Naranjo, Paola G. Vinueza, et al, "P-SEP: a prolong stable election routing algorithm for energy-limited heterogeneous fog-supported wireless sensor networks," The Journal of Supercomputing, vol. 73, no. 2, pp. 733-755, 2017. https://doi.org/10.1007/s11227-016-1785-9
  20. Baccarelli, Enzo, et al, "Fog of Everything: Energy-efficient Networked Computing Architectures, Research Challenges, and a Case Study," IEEE Access, 2017.
  21. Shojafar, Mohammad, et al, "FLAPS: bandwidth and delay-efficient distributed data searching in Fog-supported P2P content delivery networks," The Journal of Supercomputing, pp. 1-22, 2017.
  22. Shojafar, Mohammad, Nicola Cordeschi, Enzo Baccarelli, "Energy-efficient adaptive resource management for real-time vehicular cloud services," IEEE Transactions on Cloud computing, 2016.