Liu Yang, Li Yong, Cheng Wei, Wang Weiguang, Yang Junhua
School of Electronics and Information, Northwestern Polytechnical University, Xi'an 710129, China.
School of Information Engineering, Henan University of Science and Technology, Luoyang 471000, China.
Sensors (Basel). 2023 Dec 29;24(1):208. doi: 10.3390/s24010208.
Mobile crowdsensing (MCS), which is a grassroots sensing paradigm that utilizes the idea of crowdsourcing, has attracted the attention of academics. More and more researchers have devoted themselves to adopting MCS in space-air-ground-sea integrated networks (SAGSINs). Given the dynamics of the environmental conditions in SAGSINs and the uncertainty of the sensing capabilities of mobile people, the quality and coverage of the sensed data change periodically. To address this issue, we propose a novel UAV-assisted cluster-based task allocation (UCTA) algorithm for MCS in SAGSINs in a two-stage process. We first introduce the edge nodes and establish a three-layer hierarchical system with UAV-assistance, called "Platform-Edge Cluster-Participants". Moreover, an edge-aided attribute-based cluster algorithm is designed, aiming at organizing tasks into clusters, which significantly diminishes both the communication overhead and computational complexity while enhancing the efficiency of task allocation. Subsequently, a greedy selection algorithm is proposed to select the final combination that performs the sensing task in each cluster. Extensive simulations are conducted comparing the developed algorithm with the other three benchmark algorithms, and the experimental results unequivocally endorse the superiority of our proposed UCTA algorithm.
移动群智感知（MCS）作为一种利用众包理念的基层感知范式，已引起学术界的关注。越来越多的研究人员致力于在空天地海一体化网络（SAGSINs）中采用移动群智感知。鉴于SAGSINs中环境条件的动态性以及移动人群感知能力的不确定性，感知数据的质量和覆盖范围会周期性变化。为解决这一问题，我们提出了一种新颖的无人机辅助的基于簇的任务分配（UCTA）算法，用于在SAGSINs中的移动群智感知，分两个阶段进行。我们首先引入边缘节点，并在无人机辅助下建立一个三层层次系统，称为“平台 - 边缘簇 - 参与者”。此外，设计了一种基于边缘辅助属性的簇算法，旨在将任务组织成簇，这在显著减少通信开销和计算复杂度的同时提高了任务分配效率。随后，提出了一种贪婪选择算法，以选择在每个簇中执行感知任务的最终组合。进行了广泛的仿真，将所开发的算法与其他三种基准算法进行比较，实验结果明确证实了我们提出的UCTA算法的优越性。
