Resource Management and GA based scheduling for Unmanned-Aerial-Vehicles Communications
编号:18 访问权限:仅限参会人 更新:2024-07-30 16:03:02 浏览:366次 张贴报告

报告开始:2024年10月25日 15:45(Asia/Bangkok)

报告时间:5min

所在会场:[PS] Poster Session [PS] Poster

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摘要
The integration of vehicular communication and unmanned aerial vehicles (UAVs) technology has become a most trending topic and it occupies maximum of the attention of both the industrial and academic sectors. To achieve high quality communication with the ground and the air medium the aerial vehicles are connected to the cellular network so the year energy constraints are normalized. At the time of high speed data transmission the vehicles underwent certain drawbacks like delay during data uplink and high power consumption. To overcome these drawbacks in this article resource management and Generic Algorithm (GA) based scheduling (RMGAS-UAV) is developed for aerial networks based environments. The core modules of RMGAS-UAV are efficient system model and GA based drone scheduling. This models the data transmission quality of the aerial vehicles are highly improved. This network model is designed in the software called NS3 and the parameters which are taken for result calculation are data delivery ratio, network throughput, routing overhead, energy efficiency and energy consumption. From the calculated results it is shown that the RMGAS-UAV obtained better results in terms of energy efficiency and data delivery when compared with the earlier methods.
关键词
unmanned aerial vehicles (UAVs), Generic Algorithm (GA), Resource Management and Drone Scheduling.
报告人
Zahraa Hassan
Mazaya University College

稿件作者
Fatima Hashim Abbas Al-Mustaqbal University
Mohammed Habelalmateen The Islamic University
Nejood F. Abdulsattar Imam Al-Kadhum College (IKC)
Amit Gangopadhyay Mohan Babu University (Erstwhile Sree Vidyanikethan Engineering College)
Rizgar Rahman Ghafour National University of Science and Technology
Zahraa Hassan Mazaya University College
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重要日期
  • 会议日期

    10月24日

    2024

    10月27日

    2024

  • 10月14日 2024

    初稿截稿日期

  • 10月29日 2024

    注册截止日期

  • 10月31日 2024

    报告提交截止日期

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