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Computation Offloading by Two-Sided Matching in Fog Computing

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Part of the Lecture Notes in Networks and Systems book series (LNNS,volume 450)

Abstract

Fog computing extends cloud computing to the edge of the network and reduces latency. In fog computing, tasks generated by the user are allocated to fog devices to maintain load balancing. In this paper, a SPA two-sided matching algorithm, based on the student project allocation algorithm, is proposed for allocating user tasks to fog devices. The two-sided matching is intended to improve the stability of matching, and its feasibility is verified through experiments. The experimental results show that the proposed method can satisfy the requirements of matching and maximize its benefits.

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References

  1. Atzori, L., Iera, A., Morabito, G.: The Internet of Things: a survey. Comput. Netw. 54(15), 2787–2805 (2010)

    CrossRef  Google Scholar 

  2. Evans, D.: The Internet of Things: How the Next Evolution of the Internet is Changing Everything. Cisco Systems (2011)

    Google Scholar 

  3. Du, J., Zhao, L., Feng, J., et al.: Computation offloading and resource allocation in mixed fog/cloud computing systems with min-max fairness guarantee. IEEE Trans. Commun 66(4), 1–1 (2017)

    Google Scholar 

  4. Chang, Z., Zhou, Z., Ristaniemi, T., et al.: Energy efficient optimization for computation offloading in fog computing system. In: IEEE Global Communications Conference, pp. 1–6 (2017)

    Google Scholar 

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

    Google Scholar 

  6. Liu, Y., Fieldsend, J.E., Min, G.: A framework of fog computing: architecture, challenges and optimization. IEEE Access 5, 25445–25454 (2017)

    CrossRef  Google Scholar 

  7. Chiang, M., Zhang, T.: Fog and IoT: an overview of research opportunities. IEEE Internet Things J. 3(6), 854–864 (2017)

    CrossRef  Google Scholar 

  8. Aazam, M., Huh, E.N.: Fog computing micro datacenter based dynamic resource estimation and pricing model for IoT. Strojarstvo Časopis Za Teoriju I Praksu U Strojarstvu 51(5), 687–694 (2015)

    Google Scholar 

  9. Aazam, M., St-Hilaire, M., Lung, C.H., et al.: MeFoRE: QoE based resource estimation at fog to enhance QoS in IoT. In:IEEE International Conference on Telecommunications, pp. 1–5 (2016)

    Google Scholar 

  10. Aazam, M., St-Hilaire, M., Lung, C.H., et al.: PRE-Fog: IoT trace based probabilistic resource estimation at Fog. In: IEEE Consumer Communications & Networking Conference, pp. 1–17 (2016)

    Google Scholar 

  11. Do, C.T., Tran, N.H., Pham, C., et al.: A proximal algorithm for joint resource allocation and minimizing carbon footprint in geo-distributed fog computing. In: IEEE International Conference on Information Networking, pp. 324–329 (2015)

    Google Scholar 

  12. Name, H.A.M., Oladipo, F.O., Ariwa, E.: User mobility and resource scheduling and management in fog computing to support IoT devices. In: International Conference on Innovative Computing Technology, pp. 191–196 (2017)

    Google Scholar 

  13. Skarlat, O., Nardelli, M., Schulte, S., et al.: Resource provisioning for IoT services in the fog. SOCA 11(4), 427–443 (2016)

    CrossRef  Google Scholar 

  14. Gu, Y.: Matching theory framework for 5G wireless communications. Dissertation, University of Houston (2016)

    Google Scholar 

  15. Bonomi, F., Milito, R., Zhu, J., Addepalli, S.: Fog computing and its role in the internet of things. In: Fog Computing and Its Role in the Internet of Things (2012)

    Google Scholar 

  16. Lin, L., Liao, X., Jin, H., Li, P.: Computation offloading toward edge computing. Proc. IEEE 107, 1584–1607 (2019). https://doi.org/10.1109/JPROC.2019.2922285

    CrossRef  Google Scholar 

  17. Bermbach, D., et al.: Towards auction-based function placement in serverless fog platforms. In: 2020 IEEE International Conference on Fog Computing (ICFC), pp. 25–31. IEEE (2020)

    Google Scholar 

  18. Zhu, H., Huang, C., Zhou, J.: EdgeChain: blockchain-based multi-vendor mobile edge application placement. In: 2018 4th IEEE Conference on Network Softwarization and Workshops (NetSoft), Montreal, QC, pp. 222–226 (2018). https://doi.org/10.1109/NETSOFT.2018.8460035

  19. Pan, J., Wang, J., Hester, A., Alqerm, I., Liu, Y., Zhao, Y.: EdgeChain: an Edge-IoT framework and prototype based on blockchain and smart contracts. arXiv:1806.06185 (2018)

    Google Scholar 

  20. Sardellitti, S., Scutari, G., Barbarossa, S.: Joint optimization of radio and computational resources for multicell mobile-edge computing. IEEE Trans. Signal Inf. Process. Netw. 1(2), 89–103 (2015)

    MathSciNet  Google Scholar 

  21. Deng, R., Lu, R., Lai, C., Luan, T.H., Liang, H.: Optimal workload allocation in fog-cloud computing towards balanced delay and power consumption. IEEE Internet Things J. 3(6), 1171–1181 (2016)

    Google Scholar 

  22. Mukherjee, M., Kumar, S., Shojafar, M., Zhang, Q., Mavromoustakis, C.X.: Joint task offloading and resource allocation for delay-sensitive fog networks. In: ICC 2019 - 2019 IEEE International Conference on Communications (ICC), Shanghai, China, pp. 1–7 (2019)

    Google Scholar 

  23. Labidi, W., Sarkiss, M., Kamoun, M.: Energy-optimal resource scheduling and computation offloading in small cell networks. In: 2015 22nd International Conference on Telecommunications (ICT), Sydney, NSW, pp. 313–318 (2015)

    Google Scholar 

  24. You, C., Huang, K.: Multiuser resource allocation for mobile-edge computation offloading. In: Global Communications Conference, pp. 1–6 (2017)

    Google Scholar 

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Acknowledgments

Thanks to all the teachers and students who helped and supported me during my studies. Especially my teacher, Uehara teacher. Whether it is learning or essay guidance, the teacher has devoted a lot of time and energy to take this opportunity to express gratitude to the teacher.

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Correspondence to Meng Wang .

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Wang, M., Uehara, M. (2022). Computation Offloading by Two-Sided Matching in Fog Computing. In: Barolli, L., Hussain, F., Enokido, T. (eds) Advanced Information Networking and Applications. AINA 2022. Lecture Notes in Networks and Systems, vol 450. Springer, Cham. https://doi.org/10.1007/978-3-030-99587-4_9

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