灾难场景下机器人辅助自适应通信恢复方法

IF 5 2区 计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Kuangrong Hao, Chenwei Zhao, Xiaoyan Liu
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引用次数: 0

摘要

通信恢复是地震、台风、洪水等救援重建场景的必要条件。快速稳定的通信链路可以为救援过程提供高效的受害者实时信息。然而,传统的集中式通信链路无法遍历具有信息共享需求的进一步受害者。通信链路的均匀分布给拥挤的受灾地区带来了较大的负荷负担。因此,我们提出了一个由应急通信车辆、骨干链路和分支链路组成的三层架构,以通过移动机器人快速恢复通信。然后,考虑受害者的分布情况,提出了一种改进的MaxMin距离算法作为机器人调度的基础。用封闭公式估计了链路的中继概率。最后,仿真结果验证了所提算法能够以较低的时延和较高的包投递率恢复通信。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

A robot-assisted adaptive communication recovery method in disaster scenarios

A robot-assisted adaptive communication recovery method in disaster scenarios
Abstract Communication recovery is necessary for rescue and reconstruction scenarios including earthquakes, typhoons, floods, etc. The rapid and stable communication link can provide efficient victims’ real-time information for the rescue process. However, traditional centralized communication links cannot traverse the further victims with information-sharing requirements. And the even communication link distribution leads to a load burden on the crowded victim area. Thus, we propose a three-layer architecture consisting of the emergency communication vehicle, backbone links, and branch links to rapidly recover communication via mobile robots. Then, considering victims’ distribution, an improved MaxMin distance algorithm is presented as the basis of robot dispatch. The relay probability of the link is also estimated with closed formulae. Finally, simulation results verify that our proposed algorithm can recover communication with lower delay and higher packet delivery ratio.
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来源期刊
Complex & Intelligent Systems
Complex & Intelligent Systems COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-
CiteScore
9.60
自引率
10.30%
发文量
297
期刊介绍: Complex & Intelligent Systems aims to provide a forum for presenting and discussing novel approaches, tools and techniques meant for attaining a cross-fertilization between the broad fields of complex systems, computational simulation, and intelligent analytics and visualization. The transdisciplinary research that the journal focuses on will expand the boundaries of our understanding by investigating the principles and processes that underlie many of the most profound problems facing society today.
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