{"title":"Mission time minimization for UAV-supported data distribution in Internet of Things","authors":"Rui Liu, Zhenyu Na, Bowen Li, Ye Lin","doi":"10.1002/adc2.202","DOIUrl":null,"url":null,"abstract":"<p>Unmanned aerial vehicles (UAVs) have been widely used to transmit data to Internet of Things (IoT) devices in various industrial, civil and military applications because of their flexibility and mobility. Some emergency situations pose strict requirements for UAV mission completion time. Therefore, this paper investigates a UAV-supported data distribution network, where a UAV is dispatched to distribute data to a group of IoT devices. We propose a device attribution (DA) based cluster-by-cluster (CBC) communication strategy. The objective is to minimize UAV mission time while satisfying the required data amount of all devices. To this end, we propose a mission time optimization algorithm (MTOA), whose key lies in invoking DA mechanism to determine the device belonging in the coverage of overlapping clusters. Numerical results demonstrate that the proposed strategy can effectively reduce the mission time compared with the baseline ones, offering an innovative method for solving complex device attribution issues. Furthermore, the proposed strategy is expected to exhibit a significant potential in scenarios involving the high-density IoT device deployment.</p>","PeriodicalId":100030,"journal":{"name":"Advanced Control for Applications","volume":"6 3","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/adc2.202","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advanced Control for Applications","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/adc2.202","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Unmanned aerial vehicles (UAVs) have been widely used to transmit data to Internet of Things (IoT) devices in various industrial, civil and military applications because of their flexibility and mobility. Some emergency situations pose strict requirements for UAV mission completion time. Therefore, this paper investigates a UAV-supported data distribution network, where a UAV is dispatched to distribute data to a group of IoT devices. We propose a device attribution (DA) based cluster-by-cluster (CBC) communication strategy. The objective is to minimize UAV mission time while satisfying the required data amount of all devices. To this end, we propose a mission time optimization algorithm (MTOA), whose key lies in invoking DA mechanism to determine the device belonging in the coverage of overlapping clusters. Numerical results demonstrate that the proposed strategy can effectively reduce the mission time compared with the baseline ones, offering an innovative method for solving complex device attribution issues. Furthermore, the proposed strategy is expected to exhibit a significant potential in scenarios involving the high-density IoT device deployment.
无人飞行器(UAV)因其灵活性和机动性,在各种工业、民用和军事应用中被广泛用于向物联网(IoT)设备传输数据。一些紧急情况对无人飞行器完成任务的时间提出了严格要求。因此,本文研究了一种无人机支持的数据分发网络,即派遣一架无人机向一组物联网设备分发数据。我们提出了一种基于设备归属(DA)的逐簇(CBC)通信策略。其目标是在满足所有设备所需数据量的同时,最大限度地缩短无人飞行器的任务时间。为此,我们提出了一种任务时间优化算法(MTOA),其关键在于调用 DA 机制来确定重叠集群覆盖范围内的设备归属。数值结果表明,与基线策略相比,拟议策略能有效缩短任务时间,为解决复杂的设备归属问题提供了一种创新方法。此外,在涉及高密度物联网设备部署的场景中,所提出的策略有望展现出巨大的潜力。