Abstract
Multi-access Edge Computing (MEC) is attracting attention as a way of realizing the diverse services expected in 5G. Since resources of the MEC hosts are limited, optimal Application (App) allocation methods for the Distributed Cloud Environment (DCE) consisting of the MEC hosts and Central Cloud hosts are being actively studied. This paper proposes an App relocation method for the Common Service Infrastructure, which manages diverse Apps across service providers, to enhance the User Equipment accommodation efficiency of the DCE. The proposed method achieves a high success rate and efficient App relocation by selecting a combination of the relocated App and destination host while simultaneously considering the E2E delay variation of each App affected by App relocation and the cost associated with App relocation. Numerical simulations show that the proposed method reduces the number of initial App allocation failures by up to 73.6% compared to the existing method.
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References
ITU-R: IMT Vision – Framework and overall objectives of the future development of IMT for 2020 and beyond. Itu-R M.2083-0, ITU (2015)
Abbas, N., Zhang, Y., Taherkordi, A., Skeie, T.: Mobile edge computing: a survey. IEEE IoT J. 5, 450–465 (2018). IEEE
Mao, Y., You, C., Zhang, J., Huang, K., Letaief, K.B.: A survey on mobile edge computing: the communication perspective. IEEE Commun. Surv. Tut. 19, 2322–2358 (2017) . IEEE
Ahmed, A., Ahmed, E.: A survey on mobile edge computing. In: 10th International Conference on Intelligent Systems and Control, ISCO 2016, pp. 1–8. IEEE (2016)
Bellavista, P., Berrocal, J., Corradi, A., Das, S.K., Foschini, L., Zanni, A.: A survey on fog computing for the Internet of Things. Pervasive Mob. Comput. 52, 71–99 (2019). IEEE
Luo, Y., Qiu, S.: Optimal resource reservation scheme for maximizing profit of service providers in edge computing federation. In: 2019 IEEE International Conference. IEEE (2019)
Porambage, P., Okwuibe, J., Liyanage, M., Ylianttila, M., Taleb, T.: Survey on multi-access edge computing for Internet of Things realization. IEEE Commun. Surv. Tut. 20, 2961–2991 (2018). IEEE
Berno, M., Alcaraz, J.J., Rossi, M.: On the allocation of computing tasks under QoS constraints in hierarchical MEC architectures. In: International Conference on FMEC 2019, pp. 876–879. IEEE (2019)
ETSI: MEC 003 - V2.1.1 - Multi-access edge computing (MEC). Framework and Reference Architecture, Vol. 1, pp. 1–21. ETSI (2019)
Vondra, M., Becvar, Z.: QoS-ensuring distribution of computation load among cloud-enabled small cells. In: International Conference on CloudNet 2014, pp. 197–203. IEEE (2014)
Li, Q., Zhao, J., Gong, Y., Zhang, Q.: Energy-efficient computation offloading and resource allocation in fog computing for Internet of Everything. China Commun. 16, 32–41. IEEE (2019)
Zhang, W., Hu, Y., Zhang, Y., Raychaudhuri, D.: SEGUE: quality of service aware edge cloud service migration. In: International Conference on CloudCom2016, pp. 344–351. IEEE (2016)
Maheshwari, S., Choudhury, S., Seskar, I., Raychaudhuri, D.: Traffic-aware dynamic container migration for real-time support in mobile edge clouds. In: International Conference on ANTS2018, pp. 1–6. IEEE (2018)
Wang, S., Xu, J., Zhang, N., Liu, Y.: A survey on service migration in mobile edge computing. IEEE Access 6, 23511–23528 (2018). IEEE
The Linux Kernel documentation: https://www.kernel.org/doc/html/latest/scheduler/sched-design-CFS.html. The kernel development community
Acknowledgments
This work was conducted as part of the project entitled “Research and development for innovative AI network integrated infrastructure technologies (JPMI00316)” supported by the Ministry of Internal Affairs and Communications, Japan.
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Joh, T., Warabino, T., Suzuki, M., Suzuki, Y., Otani, T. (2021). Application Relocation Method for Distributed Cloud Environment Considering E2E Delay and Cost Variation. In: Barolli, L., Woungang, I., Enokido, T. (eds) Advanced Information Networking and Applications. AINA 2021. Lecture Notes in Networks and Systems, vol 226. Springer, Cham. https://doi.org/10.1007/978-3-030-75075-6_36
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DOI: https://doi.org/10.1007/978-3-030-75075-6_36
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