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Classification Aspects of the Data Offloading Process Applied to Fog Computing

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Computational Science and Its Applications – ICCSA 2021 (ICCSA 2021)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 12957))

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Abstract

The process of data offloading in fog-based environments can offer advantages such as energy savings, freeing up storage space, reduction in decision-making time, network usage reduction, among others. Thus, it is important that the data offloading process must be governed by rules and policies which will define how and when the process will be executed in the solution. Therefore, it is necessary to know the aspects of the data offloading process and discover the importance of each one of them, aiming to select the best techniques for policies definition in fog-based systems. So, this paper presents an approach through structuring in the form of a taxonomy, which classifies and organizes the knowledge needed to develop policies governing the data offloading process. Overall, fourteen (14) aspects that influence decisions for the data offloading process were classified. Finally, a practical example of how this approach can be instantiated in real-world scenarios is provided.

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References

  1. Aazam, M., Zeadally, S., Harras, K.A.: Offloading in fog computing for IoT: review, enabling technologies, and research opportunities. Future Gener. Comput. Syst. 87, 278–289 (2018)

    Article  Google Scholar 

  2. Ahn, D.J., Jeong, J., Lee, S.: A novel cloud-fog computing network architecture for big-data applications in smart factory environments. In: Gervasi, O., et al. (eds.) ICCSA 2018. LNCS, vol. 10964, pp. 520–530. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-95174-4_41

    Chapter  Google Scholar 

  3. Alelaiwi, A.: An efficient method of computation offloading in an edge cloud platform. J. Parallel Distrib. Comput. 127, 58–64 (2019)

    Article  Google Scholar 

  4. Azimi, I., Anzanpour, A., Rahmani, A.M., Liljeberg, P., Salakoski, T.: Medical warning system based on internet of things using fog computing. In: 2016 International Workshop on Big Data and Information Security (IWBIS), pp. 19–24. IEEE (2016)

    Google Scholar 

  5. Bonomi, F., Milito, R., Zhu, J., Addepalli, S.: Fog computing and its role in the internet of things. In: Proceedings of the First Edition of the MCC Workshop on Mobile Cloud Computing, pp. 13–16. ACM (2012)

    Google Scholar 

  6. Cisco, A.: Fog computing and the internet of things: extend the cloud to where the things are. [Electronic resource] (2015). https://www.cisco.com/c/dam/en_us/solutions/trends/iot/docs/computing-overview.pdf. Accessed 10 Mar 2019

  7. Dubey, H., Yang, J., Constant, N., Amiri, A.M., Yang, Q., Makodiya, K.: Fog data: enhancing telehealth big data through fog computing. In: 2015 Proceedings of the ASE Bigdata & Social Informatics, pp. 1–6. Proceedings of the ASE bigdata (2015)

    Google Scholar 

  8. Enzai, N.I.M., Tang, M.: A taxonomy of computation offloading in mobile cloud computing. In: 2014 2nd IEEE International Conference on Mobile Cloud Computing, Services, and Engineering, pp. 19–28. IEEE (2014)

    Google Scholar 

  9. Esteves, S., Silva, J., Veiga, L.: Quality-of-service for consistency of data geo-replication in cloud computing. In: Kaklamanis, C., Papatheodorou, T., Spirakis, P.G. (eds.) Euro-Par 2012. LNCS, vol. 7484, pp. 285–297. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-32820-6_29

    Chapter  Google Scholar 

  10. Fernando, N., Loke, S.W., Rahayu, W.: Mobile cloud computing: a survey. Future Gener. Comput. Syst. 29(1), 84–106 (2013)

    Article  Google Scholar 

  11. Giang, N.K., Blackstock, M., Lea, R., Leung, V.C.: Developing IoT applications in the fog: a distributed dataflow approach. In: 2015 5th International Conference on the Internet of Things (IOT), pp. 155–162. IEEE (2015)

    Google Scholar 

  12. Hao, Z., Novak, E., Yi, S., Li, Q.: Challenges and software architecture for fog computing. IEEE Internet Comput. 21(2), 44–53 (2017)

    Article  Google Scholar 

  13. He, S., Cheng, B., Wang, H., Xiao, X., Cao, Y., Chen, J.: Data security storage model for fog computing in large-scale IoT application. In: IEEE INFOCOM 2018-IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS), pp. 39–44. IEEE (2018)

    Google Scholar 

  14. Huang, C., Lu, R., Choo, K.K.R.: Vehicular fog computing: architecture, use case, and security and forensic challenges. IEEE Commun. Mag. 55(11), 105–111 (2017)

    Article  Google Scholar 

  15. Kuo, P.H., et al.: An integrated edge and fog system for future communication networks. In: 2018 IEEE Wireless Communications and Networking Conference Workshops (WCNCW), pp. 338–343. IEEE (2018)

    Google Scholar 

  16. Lee, K., Kim, D., Ha, D., Rajput, U., Oh, H.: On security and privacy issues of fog computing supported internet of things environment. In: 2015 6th International Conference on the Network of the Future (NOF), pp. 1–3. IEEE (2015)

    Google Scholar 

  17. Lee, W., Nam, K., Roh, H.G., Kim, S.H.: A gateway based fog computing architecture for wireless sensors and actuator networks. In: 2016 18th International Conference on Advanced Communication Technology (ICACT), pp. 210–213. IEEE (2016)

    Google Scholar 

  18. Mahmud, R., Kotagiri, R., Buyya, R.: Fog computing: a taxonomy, survey and future directions. In: Di Martino, B., Li, K.-C., Yang, L.T., Esposito, A. (eds.) Internet of Everything. IT, pp. 103–130. Springer, Singapore (2018). https://doi.org/10.1007/978-981-10-5861-5_5

    Chapter  Google Scholar 

  19. Maksimović, M.: Improving computing issues in internet of things driven e-health systems. In: Proceedings of the International Conference for Young Researchers in Informatics, Mathematics and Engineering 2017, pp. 14–17 (2017)

    Google Scholar 

  20. Moysiadis, V., Sarigiannidis, P., Moscholios, I.: Towards distributed data management in fog computing. Wirel. Commun. Mob. Comput. 2018, 1–14 (2018). https://doi.org/10.1155/2018/7597686

  21. OpenFog: Openfog use cases (2020). http://openfogconsortium.org/

  22. Pisani, F., do Rosario, V.M., Borin, E.: Fog vs. cloud computing: should i stay or should i go? Future Internet 11(2), 34 (2019)

    Google Scholar 

  23. Podsevalov, I., Iakushkin, O., Kurbangaliev, R., Korkhov, V.: Blockchain as a platform for fog computing. In: Misra, S., et al. (eds.) ICCSA 2019. LNCS, vol. 11620, pp. 596–605. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-24296-1_48

    Chapter  Google Scholar 

  24. Rahmani, A.M., et al.: Exploiting smart e-health gateways at the edge of healthcare internet-of-things: a fog computing approach. Future Gener. Comput. Syst. 78, 641–658 (2018)

    Article  Google Scholar 

  25. Shi, H., Chen, N., Deters, R.: Combining mobile and fog computing: using CoAP to link mobile device clouds with fog computing. In: 2015 IEEE International Conference on Data Science and Data Intensive Systems, pp. 564–571. IEEE (2015)

    Google Scholar 

  26. Silva, C.A., de Aquino Júnior, G.S.: Fog computing in healthcare: a review. In: 2018 IEEE Symposium on Computers and Communications (ISCC), pp. 1126–1131. IEEE (2018)

    Google Scholar 

  27. Silva, C.A., de Aquino Júnior, G.S., Melo, S.R.M.: A blockchain-based approach for privacy control of patient’s medical records in the fog layer. In: Anais Principais do XXV Simpósio Brasileiro de Multimídia e Web, pp. 133–136. SBC, Porto Alegre (2019). https://sol.sbc.org.br/index.php/webmedia/article/view/8011

  28. Tuli, S., Mahmud, R., Tuli, S., Buyya, R.: FogBus: a blockchain-based lightweight framework for edge and fog computing. J. Syst. Softw. 154, 22–36 (2019)

    Article  Google Scholar 

  29. Verma, S., Yadav, A.K., Motwani, D., Raw, R., Singh, H.K.: An efficient data replication and load balancing technique for fog computing environment. In: 2016 3rd International Conference on Computing for Sustainable Global Development (INDIACom), pp. 2888–2895. IEEE (2016)

    Google Scholar 

  30. Yousefpour, A., et al.: All one needs to know about fog computing and related edge computing paradigms: a complete survey. J. Syst. Archit. (2019)

    Google Scholar 

  31. Zhou, Y., Tian, L., Liu, L., Qi, Y.: Fog computing enabled future mobile communication networks: a convergence of communication and computing. IEEE Commun. Mag. 57(5), 20–27 (2019)

    Article  Google Scholar 

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Acknowledgments

This study was financed in part by the Coordenação de Aperfeiçamento de Pessoal de Nível Superior - Brasil (CAPES) - Finance Code 001.

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Authors and Affiliations

  1. Federal University of Rio Grande do Norte, Natal, 59078-970, Brazil

    Sávio Melo & Gibeon Aquino

  2. Federal Institute of Education, Science and Technology of Paraíba, Catolé do Rocha, 58884-000, Brazil

    Cícero Silva

Authors
  1. Sávio Melo
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  2. Cícero Silva
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  3. Gibeon Aquino
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Corresponding author

Correspondence to Sávio Melo .

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Editors and Affiliations

  1. University of Perugia, Perugia, Italy

    Osvaldo Gervasi

  2. University of Basilicata, Potenza, Potenza, Italy

    Beniamino Murgante

  3. Covenant University, Ota, Nigeria

    Sanjay Misra

  4. University of Cagliari, Cagliari, Italy

    Chiara Garau

  5. University of Cagliari, Cagliari, Italy

    Ivan Blečić

  6. Monash University, Clayton, VIC, Australia

    David Taniar

  7. Kyushu Sangyo University, Fukuoka, Japan

    Bernady O. Apduhan

  8. University of Minho, Braga, Portugal

    Ana Maria A. C. Rocha

  9. Polytechnic University of Bari, Bari, Italy

    Eufemia Tarantino

  10. Polytechnic University of Bari, Bari, Italy

    Carmelo Maria Torre

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Melo, S., Silva, C., Aquino, G. (2021). Classification Aspects of the Data Offloading Process Applied to Fog Computing. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2021. ICCSA 2021. Lecture Notes in Computer Science(), vol 12957. Springer, Cham. https://doi.org/10.1007/978-3-030-87013-3_26

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  • DOI: https://doi.org/10.1007/978-3-030-87013-3_26

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  • Online ISBN: 978-3-030-87013-3

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