Distributed Deep Learning for Cooperative Computation Offloading in Low Earth Orbit Satellite Networks|Qingqing Tang;Zesong Fei;Bin Li|School of Computer and Software,Nanjing University of Information Science and Technology,Nanjing 210044,China - 期刊导航|首站-论文投稿智能助手|论文发表|论文智能投稿|期刊自助发表推荐|杂志社快速发表|查同导刊-域田数据官方网站

典型文献

Distributed Deep Learning for Cooperative Computation Offloading in Low Earth Orbit Satellite Networks

文献摘要：

Low earth orbit(LEO)satellite network is an important development trend for future mobile communication systems,which can truly realize the"ubiquitous connection"of the whole world.In this paper,we present a cooperative computation offload-ing in the LEO satellite network with a three-tier com-putation architecture by leveraging the vertical coop-eration among ground users,LEO satellites,and the cloud server,and the horizontal cooperation between LEO satellites.To improve the quality of service for ground users,we optimize the computation offload-ing decisions to minimize the total execution delay for ground users subject to the limited battery capac-ity of ground users and the computation capability of each LEO satellite.However,the formulated problem is a large-scale nonlinear integer programming prob-lem as the number of ground users and LEO satel-lites increases,which is difficult to solve with general optimization algorithms.To address this challenging problem,we propose a distributed deep learning-based cooperative computation offloading(DDLCCO)algo-rithm,where multiple parallel deep neural networks(DNNs)are adopted to learn the computation offload-ing strategy dynamically.Simulation results show that the proposed algorithm can achieve near-optimal per-formance with low computational complexity com-pared with other computation offloading strategies.

文献关键词：

中图分类号：

[1] 自动化技术、计算机技术（TP） / 计算技术、计算机技术（TP3） / 计算机的应用（TP39） / 信息处理(信息加工)（TP391）

[2] 医药、卫生（R） / 基础医学（R3） / 病理学（R36） / 病理过程（R364）

[3] 天文学、地球科学（P） / 地球物理学（P3） / 空间物理（P35）

作者姓名：

Qingqing Tang;Zesong Fei;Bin Li

作者机构：

School of Information and Electronics,Beijing Institute of Technology,Beijing 100081,China;School of Computer and Software,Nanjing University of Information Science and Technology,Nanjing 210044,China;Key Lab of Broadband Wireless Communication and Sensor Network Technology,Nanjing University of Posts and Telecommunications,Ministry of Education,Nanjing 210003,China

文献出处：

中国通信（英文版）

引用格式：

[1]Qingqing Tang;Zesong Fei;Bin Li-.Distributed Deep Learning for Cooperative Computation Offloading in Low Earth Orbit Satellite Networks)[J].中国通信（英文版）,2022(04):230-243

A类：

DDLCCO

B类：

Distributed,Deep,Learning,Cooperative,Computation,Offloading,Low,Earth,Orbit,Satellite,Networks,earth,orbit,LEO,important,development,trend,future,mobile,communication,systems,which,can,truly,realize,ubiquitous,connection,whole,world,In,this,paper,present,cooperative,three,tier,architecture,by,leveraging,vertical,among,ground,users,satellites,cloud,server,horizontal,cooperation,between,To,improve,quality,service,optimize,decisions,minimize,total,execution,delay,subject,limited,battery,capac,capability,each,However,formulated,problem,large,scale,nonlinear,integer,programming,number,increases,difficult,solve,general,optimization,algorithms,address,challenging,distributed,deep,learning,offloading,where,multiple,parallel,neural,networks,DNNs,adopted,strategy,dynamically,Simulation,results,show,that,proposed,achieve,optimal,formance,low,computational,complexity,pared,other,strategies

AB值：

0.537217

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