Outage Probability Analysis for UAV-Aided Mobile Edge Computing Networks

Jun Liu; Yuwei Zhang; Jing Wang; Tao Cui; Lin Zhang; Chao Li; Kai Chen; Sun Li; Sunli Feng; Dongqing Xie; Dahua Fan; Jianghong Ou; Yun Li; Haige Xiang; Kaimeno  Dube; Abbarbas  Muazu; Nakilavai  Rono; Fusheng Zhu; Liming Chen; Wen Zhou; Zhusong Liu

doi:10.4108/eetinis.v9i31.960

Authors

Jun Liu Tsinghua University
Yuwei Zhang Tsinghua University
Jing Wang Tsinghua University
Tao Cui Tsinghua University
Lin Zhang Tsinghua University
Chao Li Hamdard University
Kai Chen Huawei Technologies (Sweden)
Sun Li Xi'an Jiaotong University
Sunli Feng King Abdullah University of Science and Technology
Dongqing Xie Anhui University of Technology
Dahua Fan Henan University of Technology
Jianghong Ou Henan University of Technology
Yun Li University of Illinois Urbana-Champaign
Haige Xiang Peking University
Kaimeno Dube Vaal University of Technology
Abbarbas Muazu Baze University
Nakilavai Rono Rongo University
Fusheng Zhu Guangdong New Generation Communication and Network Innovative Institute (GDCNi), Guangzhou, China
Liming Chen Electric Power Research Institute of CSG, Guangzhou, China
Wen Zhou Nanjing Forestry University
Zhusong Liu Anhui University of Technology

DOI:

https://doi.org/10.4108/eetinis.v9i31.960

Keywords:

UAV, mobile edge computing, outage probability, latency

Abstract

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.

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