Outage Probability Analysis for UAV-Aided Mobile Edge Computing Networks

被引:0
|
作者
Liu J. [1 ]
Zhang Y. [1 ]
Wang J. [1 ]
Cui T. [1 ]
Zhang L. [1 ]
Li C. [2 ]
Chen K. [3 ]
Li S. [4 ]
Feng S. [5 ]
Xie D. [6 ]
Fan D. [7 ,8 ]
Ou J. [7 ,8 ]
Li Y. [9 ]
Xiang H. [10 ]
Dube K. [11 ]
Muazu A. [12 ]
Rono N. [13 ]
Zhu F. [14 ]
Chen L. [15 ]
Zhou W. [16 ]
Liu Z. [17 ]
机构
[1] Information Research Center, Tsinghua University, Beijing
[2] Advanced Research Center, Hamdard University
[3] Huawei Technologies, Stockholm
[4] Information Research Center, Anhui University of Technology
[5] Henan University of Technology, Zhengzhou
[6] Starway Communication, Guangzhou
[7] University of Illinois Urbana-Champaign, Urbana
[8] Vaal University of Technology, Andries Potgieter Blvd
[9] Baze University, Airport Road, Abuja
[10] Rongo University, Rongo
[11] Guangdong New Generation Communication and Network Innovative Institute (GDCNi), Guangzhou
[12] Electric Power Research Institute of CSG, Guangzhou
[13] Nanjing Forestry University, Nanjing
[14] Anhui University of Technology, Anhui
基金
中国国家自然科学基金;
关键词
Latency; Mobile edge computing; Outage probability; Uav;
D O I
10.4108/EETINIS.V9I31.960
中图分类号
学科分类号
摘要
This paper studies one typical mobile edge computing (MEC) system, where a single user has some intensively calculating tasks to be computed by M edge nodes (ENs) with much more powerful calculating capability. In particular, unmanned aerial vehicle (UAV) can act as the ENs due to its flexibility and high mobility in the deployment. For this system, we propose several EN selection criteria to improve the system whole performance of computation and communication. Specifically, criterion I selects the best EN based on maximizing the received signal-to-noise ratio (SNR) at the EN, criterion II performs the selection according to the most powerful calculating capability, while criterion III chooses one EN randomly. For each EN selection criterion, we perform the system performance evaluation by analyzing outage probability (OP) through deriving some analytical expressions. From these expressions, we can obtain some meaningful insights regarding how to design the MEC system.We finally perform some simulation results to demonstrate the effectiveness of the proposed MEC network. In particular, criterion I can exploit the full diversity order equal to M. © 2022. Jun Liu et al., licensed to EAI. This is an open access article distributed under the terms of the Creative Commons Attribution license, which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited.
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