{"title":"Sensing Quality Constrained Packet Rate Optimization via Multi-UAV Collaborative Compression and Relay","authors":"Kaitao Meng, Xiaofan He, Deshi Li, Mingliu Liu, Chan Xu","doi":"10.1109/INFOCOMWKSHPS51825.2021.9484626","DOIUrl":null,"url":null,"abstract":"Due to the on-demand deployable and flexible-observation features, unmanned aerial vehicles (UAVs) is considered as one of the key enabling techniques in next-generation sensing systems. In many sensing applications (e.g., disaster rescue and environment monitoring), a single UAV is not sufficient to fulfill the requirements of transmission delay and sensing quality. Considering this, a multi-UAV collaborative compression and relaying scheme is proposed in this work. The sensory data is packed according to the sensing quality requirement and the sensory data packet rate can be maximized to improve the freshness of the sensory data. To tackle the non-convex problem of finding the optimal compression ratios and UAVs locations with packet rate maximization, the considered problem is converted into a monotonic optimization (MO) by deriving the closed-form expression of the optimal compression ratio for given UAV locations. Then, by exploiting the inherent structure of the optimal UAV locations, a novel region-elimination-based fast location search algorithm is proposed, which can effectively avoid unnecessary search and achieve a substantially faster convergence as compared to the standard MO algorithm. Besides, numerical simulations are conducted to validate the effectiveness of the proposed scheme.","PeriodicalId":109588,"journal":{"name":"IEEE INFOCOM 2021 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)","volume":"70 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE INFOCOM 2021 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/INFOCOMWKSHPS51825.2021.9484626","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
Due to the on-demand deployable and flexible-observation features, unmanned aerial vehicles (UAVs) is considered as one of the key enabling techniques in next-generation sensing systems. In many sensing applications (e.g., disaster rescue and environment monitoring), a single UAV is not sufficient to fulfill the requirements of transmission delay and sensing quality. Considering this, a multi-UAV collaborative compression and relaying scheme is proposed in this work. The sensory data is packed according to the sensing quality requirement and the sensory data packet rate can be maximized to improve the freshness of the sensory data. To tackle the non-convex problem of finding the optimal compression ratios and UAVs locations with packet rate maximization, the considered problem is converted into a monotonic optimization (MO) by deriving the closed-form expression of the optimal compression ratio for given UAV locations. Then, by exploiting the inherent structure of the optimal UAV locations, a novel region-elimination-based fast location search algorithm is proposed, which can effectively avoid unnecessary search and achieve a substantially faster convergence as compared to the standard MO algorithm. Besides, numerical simulations are conducted to validate the effectiveness of the proposed scheme.