BLOCK-ML: Blockchain and Machine Learning for UAV-BSs Deployment

Asad Aftab, Nouman Ashraf, Hassaan Khaliq Qureshi, Syed Ali Hassan, Sobia Jangsher

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

Unmanned aerial vehicles (UAVs) are expected to be extensively used as an integral part in the future generations of communication networks, to provide ubiquitous connectivity. The mobile nature of UAVs make them a tempting candidate to provide seamless connectivity in environments where the installation of conventional terrestrial base stations (BS) is not feasible. Nonetheless, there are major deployment issues related to optimal placement of UAV-mounted base stations (UAV-BSs) due to limited number of UAV-BSs, limited energy availability and trade-off between coverage area and its altitude. In this paper, we address UAV-BSs placement issues by proposing a novel Machine learning (ML) based intelligent deployment mechanism. More specifically, for intelligent deployment of UAV-BSs based on energy, computational power, nature of available data and criticality of the scenario, we use two different approaches: Support Vector Machine (SVM) and Deep Learning (DL), which is composed of sequential time series learning process. Moreover, to address the security and privacy challenges emanating from the wireless connectivity and untrusted broadcast nature of UAV-BSs, we propose a Blockchain-based novel information-sharing scheme. To evaluate the performance of our combined secure and intelligent proposed approach, we have improved energy consumption by almost twice in contrast with the normal deployment of UAV-BSs.

Original languageEnglish
Title of host publication2020 IEEE 92nd Vehicular Technology Conference, VTC 2020-Fall - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728194844
DOIs
Publication statusPublished - Nov 2020
Event92nd IEEE Vehicular Technology Conference, VTC 2020-Fall - Virtual, Victoria, Canada
Duration: 18 Nov 2020 → …

Publication series

NameIEEE Vehicular Technology Conference
Volume2020-November
ISSN (Print)1550-2252

Conference

Conference92nd IEEE Vehicular Technology Conference, VTC 2020-Fall
Country/TerritoryCanada
CityVirtual, Victoria
Period18/11/2020 → …

Keywords

  • Blockchain
  • Deep Learning
  • Machine Learning
  • UAV-BSs

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