Saugata Roy , Nabajyoti Mazumdar , Rajendra Pamula
{"title":"面向大规模物联网环境下协同数据采集的多库预置无人机群轨迹优化方案","authors":"Saugata Roy , Nabajyoti Mazumdar , Rajendra Pamula","doi":"10.1016/j.adhoc.2025.103974","DOIUrl":null,"url":null,"abstract":"<div><div>Due to autonomous flying ability and high manoeuvrability, unmanned aerial vehicle (UAV) assisted sensory data acquisition is becoming prevalent in outdoor IoT applications. However, UAV’s limited onboard power source results in a restricted flight time, necessitating the use of a multi-UAV platform to ensure uninterrupted service in a large-scale network. Nonetheless, very few studies have considered the use of multiple UAVs from distinct depots to improve network coverage with an optimal UAV swarm. This article investigates a multi-depot, energy-constrained vehicle routing problem (MDEVRP) where a fleet of UAVs is dispatched from different depots to collect sensory data from the ground nodes, provided that UAVs never run out of energy. Our objective is to discover an optimal set of UAVs with detailed hovering and travelling plans, which is an NP-hard problem. To solve such a computationally hard problem, we first leverage the variable dimensional particle swarm optimization (VD-PSO) algorithm that jointly optimizes the number of UAVs deployed, their depots, and association with the hovering locations. Then, minimal cost UAV trajectories are established, which preserves data freshness at the UAV depots. Simulation results manifest the dominance of the proposed scheme over the related state-of-the-art protocols.</div></div>","PeriodicalId":55555,"journal":{"name":"Ad Hoc Networks","volume":"178 ","pages":"Article 103974"},"PeriodicalIF":4.8000,"publicationDate":"2025-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A multi-depot provisioned UAV swarm trajectory optimization scheme for collaborative data acquisition in a large-scale IoT environment\",\"authors\":\"Saugata Roy , Nabajyoti Mazumdar , Rajendra Pamula\",\"doi\":\"10.1016/j.adhoc.2025.103974\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Due to autonomous flying ability and high manoeuvrability, unmanned aerial vehicle (UAV) assisted sensory data acquisition is becoming prevalent in outdoor IoT applications. However, UAV’s limited onboard power source results in a restricted flight time, necessitating the use of a multi-UAV platform to ensure uninterrupted service in a large-scale network. Nonetheless, very few studies have considered the use of multiple UAVs from distinct depots to improve network coverage with an optimal UAV swarm. This article investigates a multi-depot, energy-constrained vehicle routing problem (MDEVRP) where a fleet of UAVs is dispatched from different depots to collect sensory data from the ground nodes, provided that UAVs never run out of energy. Our objective is to discover an optimal set of UAVs with detailed hovering and travelling plans, which is an NP-hard problem. To solve such a computationally hard problem, we first leverage the variable dimensional particle swarm optimization (VD-PSO) algorithm that jointly optimizes the number of UAVs deployed, their depots, and association with the hovering locations. Then, minimal cost UAV trajectories are established, which preserves data freshness at the UAV depots. Simulation results manifest the dominance of the proposed scheme over the related state-of-the-art protocols.</div></div>\",\"PeriodicalId\":55555,\"journal\":{\"name\":\"Ad Hoc Networks\",\"volume\":\"178 \",\"pages\":\"Article 103974\"},\"PeriodicalIF\":4.8000,\"publicationDate\":\"2025-07-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Ad Hoc Networks\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1570870525002227\",\"RegionNum\":3,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, INFORMATION SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Ad Hoc Networks","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1570870525002227","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
A multi-depot provisioned UAV swarm trajectory optimization scheme for collaborative data acquisition in a large-scale IoT environment
Due to autonomous flying ability and high manoeuvrability, unmanned aerial vehicle (UAV) assisted sensory data acquisition is becoming prevalent in outdoor IoT applications. However, UAV’s limited onboard power source results in a restricted flight time, necessitating the use of a multi-UAV platform to ensure uninterrupted service in a large-scale network. Nonetheless, very few studies have considered the use of multiple UAVs from distinct depots to improve network coverage with an optimal UAV swarm. This article investigates a multi-depot, energy-constrained vehicle routing problem (MDEVRP) where a fleet of UAVs is dispatched from different depots to collect sensory data from the ground nodes, provided that UAVs never run out of energy. Our objective is to discover an optimal set of UAVs with detailed hovering and travelling plans, which is an NP-hard problem. To solve such a computationally hard problem, we first leverage the variable dimensional particle swarm optimization (VD-PSO) algorithm that jointly optimizes the number of UAVs deployed, their depots, and association with the hovering locations. Then, minimal cost UAV trajectories are established, which preserves data freshness at the UAV depots. Simulation results manifest the dominance of the proposed scheme over the related state-of-the-art protocols.
期刊介绍:
The Ad Hoc Networks is an international and archival journal providing a publication vehicle for complete coverage of all topics of interest to those involved in ad hoc and sensor networking areas. The Ad Hoc Networks considers original, high quality and unpublished contributions addressing all aspects of ad hoc and sensor networks. Specific areas of interest include, but are not limited to:
Mobile and Wireless Ad Hoc Networks
Sensor Networks
Wireless Local and Personal Area Networks
Home Networks
Ad Hoc Networks of Autonomous Intelligent Systems
Novel Architectures for Ad Hoc and Sensor Networks
Self-organizing Network Architectures and Protocols
Transport Layer Protocols
Routing protocols (unicast, multicast, geocast, etc.)
Media Access Control Techniques
Error Control Schemes
Power-Aware, Low-Power and Energy-Efficient Designs
Synchronization and Scheduling Issues
Mobility Management
Mobility-Tolerant Communication Protocols
Location Tracking and Location-based Services
Resource and Information Management
Security and Fault-Tolerance Issues
Hardware and Software Platforms, Systems, and Testbeds
Experimental and Prototype Results
Quality-of-Service Issues
Cross-Layer Interactions
Scalability Issues
Performance Analysis and Simulation of Protocols.