Page 106 - Proceedings of the 2018 ITU Kaleidoscope

‎ 2018 ITU Kaleidoscope Academic Conference‎

Computing Conference (IWCMC), June 2017, pp.
957–962.

[4] M. G. R. Alam, Y. K. Tun, and C. S. Hong, “Multi-agent
and reinforcement learning based code offloading
in mobile fog,” in 2016 International Conference
on Information Networking (ICOIN), Jan 2016, pp.
285–290.
[5] ETSI, “Mobile edge computing (mec); framework and
reference architecture,” March 2016.
[6] ETSI, “Mobile edge computing (mec); service
scenarios,” Tech. Rep., November 2015.
[7] X. Xia, K. Xu, Y. Wang, and Y. Xu, “A 5g-enabling
technology: Benefits, feasibility, and limitations
of in-band full-duplex mmimo,” IEEE Vehicular
Technology Magazine, pp. 1–1, 2018.
[8] J. Li, Z. Zhao, and R. Li, “Machine learning-based ids
for software-defined 5g network,” IET Networks, vol. 7,
no. 2, pp. 53–60, 2018.

[9] Stuart J. Russell and Peter Norvig, Artificial Intelligence
- A Modern Approach (3. internat. ed.), Pearson
Education, 2010.
[10] Mnih Volodymyr et al., “Human-level control through
deep reinforcement learning,” Nature, vol. 518, no.
7540, pp. 529–533, Feb. 2015.

[11] András Varga and Rudolf Hornig, “An overview of
the omnet++ simulation environment,” in Proceedings
of the 1st International Conference on Simulation
Tools and Techniques for Communications, Networks
and Systems & Workshops, ICST, Brussels, Belgium,
Belgium, 2008, Simutools ’08, pp. 60:1–60:10, ICST
(Institute for Computer Sciences, Social-Informatics
and Telecommunications Engineering).

[12] A. Virdis, G. Stea, and G. Nardini, “Simulte - a modular
system-level simulator for lte/lte-a networks based
on omnet++,” in 2014 International Conference on
Simulation and Modeling Methodologies, Technologies
and Applications (SIMULTECH), Aug. 2014, vol. 00,
pp. 59–70.

[13] François Chollet et al., “Keras,” https://keras.io,
2015.

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