Abstract
Recently, Multi-Access Edge Computing (MEC), which has been emerged as a key technology in 5G networks, enhances computation capabilities and power limitations of mobile devices (MDs) by offloading computation task to the nearby MEC servers. However, offloading the computation tasks can increase network traffics and incur extra delays. Most existing approaches focus on the computation offloading with multi-user single-MEC scenarios to decrease energy consumption and latency of the MDs. Towards this goal, we investigate a computation offloading strategy for two-tier 5G heterogeneous networks integrated with multi-MEC. In addition, we propose a random offloading search algorithm, called ROSA, that rapidly achieve the minimized energy consumption of the system considering the computation offloading decision strategies. Simulation results show that our proposed algorithm based on offloading scheme outperforms other two schemes in terms of energy consumption.
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Acknowledgments
This research was supported by the MSIT (Ministry of Science and ICT), Korea, under the Grand Information Technology Research Center support program (IITP-2018-2015-0-00742) and the National Program for Excellence in SW (2017-0-00093), supervised by the IITP (Institute for Information & communications Technology Promotion).
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Huynh, L.N.T., Pham, QV., Nguyen, Q.D., Pham, XQ., Nguyen, V., Huh, EN. (2019). Energy-Efficient Computation Offloading with Multi-MEC Servers in 5G Two-Tier Heterogeneous Networks. In: Lee, S., Ismail, R., Choo, H. (eds) Proceedings of the 13th International Conference on Ubiquitous Information Management and Communication (IMCOM) 2019. IMCOM 2019. Advances in Intelligent Systems and Computing, vol 935. Springer, Cham. https://doi.org/10.1007/978-3-030-19063-7_11
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DOI: https://doi.org/10.1007/978-3-030-19063-7_11
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