Page 93 - ITU Journal Future and evolving technologies – Volume 2 (2021), Issue 2

ITU Journal on Future and Evolving Technologies, Volume 2 (2021), Issue 2

[91] S. Guo, B. Xiao, Y . Yang, and Y . Yang. “Energy‑ [103] Y . K. Tun, Y . M. Park, N. H. Tran, W. Saad, S. R.

icient dynamic loading and resource Pandey, and C. S. Hong. icient Re‑

scheduling in mobile cloud computing”. In: IEEE source Management in UAV‑Assisted Mobile Edge
INFOCOM 2016 ‑ The 35th Annual IEEE Interna‑ Computing”. In: IEEE Communications Letters 25

tional Conference on Computer Communications. (2021).
2016.
[104] Q. Hu, Y . Cai, G. Yu, Z. Qin, M. Zhao, and G. Y .

[92] Y . Wang, Z. ‑Y . Ru, K. Wang, and P . ‑Q. Huang. Li. “Joint loading and Trajectory Design for

“Joint Deployment and Task Scheduling Optimiza‑ UAV‑Enabled Mobile Edge Computing Systems”.

tion for Large‑Scale Mobile Users in Multi‑UAV‑ In: IEEE Internet of Things Journal (2019).

Enabled Mobile Edge Computing”. In: IEEE Tran-
sactions on Cybernetics (2020). [105] F . Zhou, Y . Wu, R. Q. Hu, and Y . Qian. “Computa‑

tion Rate Maximization in UAV‑Enabled Wireless‑
[93] M. S. Elbamby, C. Perfecto, C.‑F. Liu, J. Park,

Powered Mobile‑Edge Computing Systems”. In:

S. Samarakoon, X. Chen, and M. Bennis. “Wire‑ IEEE Journal on Selected Areas in Communications

less Edge Computing With Latency and Reliabi- 36 (2018).

lity Guarantees”. In: Proceedings of the IEEE

107 (2019). [106] Y . Qian, F . Wang, J. Li, L. Shi, K. Cai, and F . Shu. “User
Association and Path Planning for UAV‑Aided Mo‑
[94] D. O hmann, M. Simsek, and G. P . Fettweis. “Achie-
bile Edge Computing With Energy Restriction”. In:
ving high availability in wireless networks IEEE Wireless Communications Letters 8 (2019).

by an optimal number of Rayleigh‑fading links”.

In: 2014 IEEE Globecom Workshops (GC [107] S. Wan, J. Lu, P . Fan, and K. B. Letaief. “Toward

Wkshps). 2014. Big Data Processing in IoT: Path Planning and

Resource Management of UAV Base Stations in

[95] M. A. Mahmood, W. K.G. Seah, and I. Welch. “Re‑ Mobile‑Edge Computing System”. In: IEEE Inter‑

liability in wireless sensor networks: A survey

net of Things Journal 7 (2020).
and challenges ahead”. In: Computer Networks 79
(2015). [108] L. Yang, H. Yao, J. Wang, C. Jiang, A. Benslimane,

[96] M. Bennis, M. Debbah, and H. V . Poor. “Ultrare- and Y . Liu. “Multi‑UAV‑Enabled Load‑Balance

liable and Low‑Latency Wireless Commu- Mobile‑Edge Computing for IoT Networks”. In:
nication: Tail, Risk, and Scale”. In: Proceedings of IEEE Internet of Things Journal (2020).
the IEEE 106 (2018).
[109] G. Wu, Y . Miao, Y . Zhang, and A. Barnawi. “Energy

[97] S. P . Boyd, N. Parikh, E. Chu, B. Peleato, and J. ef icient for UAV‑enabled mobile edge computing

Eckstein. “Distributed Optimization and Statisti‑ networks: Intelligent task prediction and of loa-
cal Learning via the Alternating Direction Method ding”. In: Comput. Commun. 150 (2020).

of Multipliers”. In: Found. Trends Mach. Learn. 3

(2011). [110] Y . Chen and Z. Zheng. “Joint Deployment and
Task Computation of UAVs in UAV‑assisted
[98] N. Buchbinder, S. Chen, and J. Naor. “Competitive 2020 21st
Edge Computing Network”. In:
Analysis via Regularization”. In: SODA. 2014. Asia‑Paci ic Network Operations and Management
[99] Z. Li and Q. Zhu. “Genetic Algorithm‑Based Op‑ Symposium (APNOMS). 2020.

timization of Of loading and Resource Allocation
[111] J. Wang, K. Liu, and J. Pan. “Online

in Mobile‑Edge Computing”. In: Information 11

(2020). UAV‑Mounted Edge Server Dispatching for
Mobile‑to‑Mobile Edge Computing”. In: IEEE

[100] L. Wan, L. Sun, X. Kong, Y . Yuan, K. Sun, and F . Internet of Things Jour‑ nal 7 (2020).

Xia. “Task‑Driven Resource Assignment in Mobile

Edge Computing Exploiting Evolutionary Com‑ [112] M. Razaviyayn, M. Hong, Z. Luo, and J. Pang. “Par‑

putation”. In: IEEE Wireless Communications 26 allel Successive Convex Approximation for Nons‑
(2019). mooth Nonconvex Optimization”. In: NIPS. 2014.

[101] M. Bowling and M. Veloso. “Multiagent learning [113] D. S. Hochbaum and A. Pathria. “Analysis of the

using a variable learning rate”. In: Arti icial Intel‑ greedy approach in problems of maximum k‑

ligence 136 (2002). coverage”. In: Naval Research Logistics (NRL) 45

[102] M. Li, N. Cheng, J. Gao, Y . Wang, L. Zhao, and X. (1998).
Shen. “Energy‑Ef icient UAV‑Assisted Mobile Edge

[114] B. Javidy, A. Hatamlou, and S. Mirjalili. “Ions

Computing: Resource Allocation and Trajectory

Optimization”. In: IEEE Transactions on Vehicular motion algorithm for solving optimization prob‑
Technology 69 (2020). lems”. In: Applied Soft Computing 32 (2015).
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