Frisbee: An Efficient Data Sharing Framework for UAV Swarms

IF 6.7 2区 计算机科学 Q1 ENGINEERING, MULTIDISCIPLINARY
Peipei Chen;Lailong Luo;Deke Guo;Qianzhen Zhang;Xueshan Luo;Bangbang Ren;Yulong Shen
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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.
飞盘无人机群的高效数据共享框架
如今,由于具有通信、计算、存储、联网和传感能力,无人驾驶飞行器(UAV)群有望在紧急情况、灾难和军事情况下发挥作用。此外,在这种情况下,每个无人飞行器都会利用其摄像头和传感器生成本地传感数据。无人机群的数据共享是用户和管理员的迫切需要。对于用户来说,他们可能希望按需访问存储在任何特定无人机上的数据。对于管理员来说,他们需要构建全局信息和态势感知,以实现多种合作应用。本文通过一个名为 Frisbee 的高效数据共享框架迈出了解决这一公开问题的第一步。它首先将所有无人飞行器分组为一系列单元,每个单元都有一个头部无人飞行器。在任何单元内,所有无人飞行器都可以直接相互通信。因此,在小区内共享方面,Frisbee 为头部无人机设计了动态布谷鸟摘要,以准确索引小区内的所有数据。在小区间共享方面,Frisbee 设计了一种有效的方法,将数据索引和头部无人机映射到一个二维虚拟平面上。在此虚拟平面的基础上,根据各机头的通信范围形成机头-无人机通信图,用于数据定位和传输。综合实验结果表明,与地面网络最复杂的方案相比,Frisbee 的插入吞吐量提高了 14.7%,响应延迟降低了 39.1%,执行开销减少了 41.4%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
IEEE Transactions on Network Science and Engineering
IEEE Transactions on Network Science and Engineering Engineering-Control and Systems Engineering
CiteScore
12.60
自引率
9.10%
发文量
393
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.
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