摘要
聚焦陆战场信息系统设计问题,结合分布式计算最新成果,基于“云网端”融合理念,构建了一套适用于分布式战场节点和智能需求的信息系统架构.针对所构建架构中,智能应用和智能性提升的关键需求,综合分布式陆战场节点资源受限、任务多样等特点,在分层联邦学习基础上,依据资源状况进行自适应调整,提供资源开销和智能提升相均衡的使用途径.经实验验证,该架构和方法效果良好,更能适应分布式条件下陆战场节点智能性需求。
Focusing on the design of land battlefield information system,combined with the latest achievements of distributed computing,based on the concept of"cloud-network-end"fusion,a set of information system architecture suitable for distributed battlefield nodes and intelligent requirements is constructed.Aiming at the key requirements of intelligent application and enhancement in the constructed architecture,such characteristics as constrained distributed land battlefield node resources,diversified tasks,etc are synthesized,and on the basis of hierarchical federal learning,self-adaptive adjustment is done according to the status of resources.The operation means for keeping the balance between the resource expenditure and intelligence improvement are provided.It has been verified by experiments that the proposed architecture and method have better results,and can better adapt to the intelligence requirements of land battlefield nodes under distributed conditions.
作者
王军
张雄涛
赵兴利
钟正仪
朱晓敏
WANG Jun;ZHANG Xiongtao;ZHAO Xingli;ZHONG Zhengyi;ZHU Xiaomin(Unit 32366 of PLA,Beijing 100042,China;School of System Engineering,National University of Defense Technology,Changsha Hunan 410072,China;Unit 66736 of PLA,Beijing 100041,China)
出处
《指挥与控制学报》
CSCD
2023年第2期192-203,共12页
Journal of Command and Control
基金
国家自然科学基金(61872378),湖南省杰出青年基金(2018JJ1032),国防科技大学科学研究项目(ZK19-03)资助。
关键词
分布作战
智能信息系统
“云网端”融合
分层联邦学习
distributed operation
intelligent information system
"cloud-network-end"fusion
hierarchical federal learning
