{"title":"Frisbee: An Efficient Data Sharing Framework for UAV Swarms","authors":"Peipei Chen;Lailong Luo;Deke Guo;Qianzhen Zhang;Xueshan Luo;Bangbang Ren;Yulong Shen","doi":"10.1109/TNSE.2024.3479695","DOIUrl":null,"url":null,"abstract":"Nowadays, owing to the communication, computation, storage, networking, and sensing abilities, the swarm of unmanned aerial vehicles (UAV) is highly anticipated to be helpful for emergency, disaster, and military situations. Additionally, in such situations, each UAV generates local sensing data with its cameras and sensors. Data sharing in UAV swarm is an urgent need for both users and administrators. For users, they may want to access data stored on any specific UAV on demand. For administrators, they need to construct global information and situational awareness to enable many cooperative applications. This paper makes the first step to tackling this open problem with an efficient data-sharing framework called Frisbee. It first groups all UAVs as a series of cells, each of which has a head-UAV. Inside any cell, all UAVs can communicate with each other directly. Thus, for the intra-cell sharing, Frisbee designs the Dynamic Cuckoo Summary for the head-UAV to accurately index all data inside the cell. For inter-cell sharing, Frisbee designs an effective method to map both the data indices and the head-UAV into a 2-dimensional virtual plane. Based on such virtual plane, a head-UAV communication graph is formed according to the communication range of each head for both data localization and transmission. The comprehensive experiments show that Frisbee achieves 14.7% higher insert throughput, 39.1% lower response delay, and 41.4% less implementation overhead, respectively, compared to the most involved solutions of the ground network.","PeriodicalId":54229,"journal":{"name":"IEEE Transactions on Network Science and Engineering","volume":"11 6","pages":"5380-5393"},"PeriodicalIF":6.7000,"publicationDate":"2024-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Network Science and Engineering","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10716497/","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
Abstract
Nowadays, owing to the communication, computation, storage, networking, and sensing abilities, the swarm of unmanned aerial vehicles (UAV) is highly anticipated to be helpful for emergency, disaster, and military situations. Additionally, in such situations, each UAV generates local sensing data with its cameras and sensors. Data sharing in UAV swarm is an urgent need for both users and administrators. For users, they may want to access data stored on any specific UAV on demand. For administrators, they need to construct global information and situational awareness to enable many cooperative applications. This paper makes the first step to tackling this open problem with an efficient data-sharing framework called Frisbee. It first groups all UAVs as a series of cells, each of which has a head-UAV. Inside any cell, all UAVs can communicate with each other directly. Thus, for the intra-cell sharing, Frisbee designs the Dynamic Cuckoo Summary for the head-UAV to accurately index all data inside the cell. For inter-cell sharing, Frisbee designs an effective method to map both the data indices and the head-UAV into a 2-dimensional virtual plane. Based on such virtual plane, a head-UAV communication graph is formed according to the communication range of each head for both data localization and transmission. The comprehensive experiments show that Frisbee achieves 14.7% higher insert throughput, 39.1% lower response delay, and 41.4% less implementation overhead, respectively, compared to the most involved solutions of the ground network.
期刊介绍:
The proposed journal, called the IEEE Transactions on Network Science and Engineering (TNSE), is committed to timely publishing of peer-reviewed technical articles that deal with the theory and applications of network science and the interconnections among the elements in a system that form a network. In particular, the IEEE Transactions on Network Science and Engineering publishes articles on understanding, prediction, and control of structures and behaviors of networks at the fundamental level. The types of networks covered include physical or engineered networks, information networks, biological networks, semantic networks, economic networks, social networks, and ecological networks. Aimed at discovering common principles that govern network structures, network functionalities and behaviors of networks, the journal seeks articles on understanding, prediction, and control of structures and behaviors of networks. Another trans-disciplinary focus of the IEEE Transactions on Network Science and Engineering is the interactions between and co-evolution of different genres of networks.