A Distributed Algorithm for UAV Cluster Task Assignment Based on Sensor Network and Mobile Information

被引:7
作者
Yang, Jian [1 ]
Huang, Xuejun [1 ]
机构
[1] Natl Univ Def Technol, Coll Elect Engn, Hefei 230031, Peoples R China
来源
APPLIED SCIENCES-BASEL | 2023年 / 13卷 / 06期
关键词
clustering; sensor network; state learning; task assignment; UAV; ENERGY-EFFICIENT;
D O I
10.3390/app13063705
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
Cluster formation and task processing are standard features for leveraging the performance of unmanned aerial vehicles (UAVs). As the UAV network is aided by sensors, functions such as clustering, reformation, and autonomous working are adaptively used for dense task processing. In consideration of the distributed nature of the UAV network coupled with wireless sensors, this article introduces a Rational Clustering Method (RCM) using dense task neighbor information exchange. The Rational Clustering Method (RCM) is an algorithm for dense task neighbor information exchange that can be used to cluster objects according to their shared properties. Each object's task neighbors, and the similarities between them, are calculated using this method. Starting with the task density of its neighbors, the RCM algorithm gives each object in the dataset a weight. This information exchange process identifies a UAV units' completing tasks and free slots. Using this information, high-slot UAVs within the communication range can be grouped as clusters. Unlike wireless sensor clusters, task allocation is performed on the basis of available slots and UAV longevity within the cluster; this prevents task incompletion/failures and delays in a densely populated UAV scenario. Cluster sustainability or dispersion is recommended when using distributed state learning. State learning transits between the pending task and UAV longevity; an intermediate state is defined for task reassignment amid immediate cluster deformation. This triple feature-based distributed method balances tasks between failures, overloading, and idle UAVs. The RCM was verified using task processing rate, completion ratio, reassignment, failures, and delay. Task processing rate was increased by 8.16% and completion ratio was increased by 10.3% with the proposed RCM-IE. Reassignment, failure, and delay were all reduced by 12.5%, 9.87%, and 11.99%, respectively, using this method.
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页数:17
相关论文
共 29 条
  • [1] A Collaborative Learning-Based Algorithm for Task Offloading in UAV-Aided Wireless Sensor Networks
    Al-Share, Rama
    Shurman, Mohammad
    Alma'aitah, Abdallah
    [J]. COMPUTER JOURNAL, 2021, 64 (10) : 1575 - 1583
  • [2] Amar Mohamed Abdellahi, 2020, Procedia Computer Science, V176, P3191, DOI 10.1016/j.procs.2020.09.130
  • [3] [Anonymous], AERIAL SEMANTIC SEGM
  • [4] Energy and task completion time minimization algorithm for UAVs-empowered MEC SYSTEM
    Asim, Muhammad
    Mashwani, Wali Khan
    Abd El-Latif, Ahmed A.
    [J]. SUSTAINABLE COMPUTING-INFORMATICS & SYSTEMS, 2022, 35
  • [5] Multi-objective clustering analysis via combinatorial pigeon inspired optimization
    Chen, Lin
    Duan, HaiBin
    Fan, YanMing
    Wei, Chen
    [J]. SCIENCE CHINA-TECHNOLOGICAL SCIENCES, 2020, 63 (07) : 1302 - 1313
  • [6] Dynamic Tasks Scheduling Model of UAV Cluster Based on Flexible Network Architecture
    Duan, Ting
    Wang, Weiping
    Wang, Tao
    Chen, Xiaofan
    Li, Xiaobo
    [J]. IEEE ACCESS, 2020, 8 (08): : 115448 - 115460
  • [7] Energy-efficient task scheduling and physiological assessment in disaster management using UAV-assisted networks
    Ejaz, Waleed
    Ahmed, Arslan
    Mushtaq, Aliza
    Ibnkahla, Mohamed
    [J]. COMPUTER COMMUNICATIONS, 2020, 155 : 150 - 157
  • [8] UAVs's efficient controlled mobility management for mobile heterogeneous wireless sensor networks
    Guezouli, Lyamine
    Barka, Kamel
    Djehiche, Asma
    [J]. JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES, 2022, 34 (06) : 2461 - 2470
  • [9] STMTO: A smart and trust multi-UAV task offloading system
    Guo, Jialin
    Huang, Guosheng
    Li, Qiang
    Xiong, Neal N.
    Zhang, Shaobo
    Wang, Tian
    [J]. INFORMATION SCIENCES, 2021, 573 : 519 - 540
  • [10] Stochastic Task Scheduling in UAV-Based Intelligent On-Demand Meal Delivery System
    Huang, Haiping
    Hu, Chengxi
    Zhu, Jie
    Wu, Min
    Malekian, Reza
    [J]. IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2022, 23 (08) : 13040 - 13054