inis 22(31): 4

Research Article

Outage Probability Analysis for UAV-Aided Mobile Edge Computing Networks

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  • @ARTICLE{10.4108/eetinis.v9i31.960,
        author={Jun Liu  and Jing Wang  and Kai Chen and Sunli Feng and Dahua Fan and Jianghong Ou and Fusheng Zhu and Liming Chen and Wen Zhou and Zhusong Liu},
        title={Outage Probability Analysis for UAV-Aided Mobile Edge Computing Networks},
        journal={EAI Endorsed Transactions on Industrial Networks and Intelligent Systems},
        volume={9},
        number={31},
        publisher={EAI},
        journal_a={INIS},
        year={2022},
        month={6},
        keywords={UAV, mobile edge computing, outage probability, latency},
        doi={10.4108/eetinis.v9i31.960}
    }
    
  • Jun Liu
    Jing Wang
    Kai Chen
    Sunli Feng
    Dahua Fan
    Jianghong Ou
    Fusheng Zhu
    Liming Chen
    Wen Zhou
    Zhusong Liu
    Year: 2022
    Outage Probability Analysis for UAV-Aided Mobile Edge Computing Networks
    INIS
    EAI
    DOI: 10.4108/eetinis.v9i31.960
Jun Liu 1, Jing Wang 1, Kai Chen2,*, Sunli Feng3, Dahua Fan4, Jianghong Ou4, Fusheng Zhu5, Liming Chen6, Wen Zhou7, Zhusong Liu8
  • 1: Tsinghua University
  • 2: Huawei Technologies (Sweden)
  • 3: King Abdullah University of Science and Technology
  • 4: Henan University of Technology
  • 5: Guangdong New Generation Communication and Network Innovative Institute (GDCNi), Guangzhou, China
  • 6: Electric Power Research Institute of CSG, Guangzhou, China
  • 7: Nanjing Forestry University
  • 8: Anhui University of Technology
*Contact email: kchen.huawei@ieee.org

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.