Joint Computing and Communication Resource Allocation for Satellite Communication Networks with Edge Computing

Shanghong Zhang; Gaofeng Cui; Yating Long; Weidong Wang

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Joint Computing and Communication Resource Allocation for Satellite Communication Networks with Edge Computing

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摘要

Benefit from the enhanced onboard processing capacities and high-speed satellite-terrestrial links,satellite edge computing has been regarded as a promising technique to facilitate the execution of the computation-intensive applications for satellite communication networks(SCNs).By deploying edge computing servers in satellite and gateway stations,SCNs can achieve significant performance gains of the computing capacities at the expense of extending the dimensions and complexity of resource management.Therefore,in this paper,we investigate the joint computing and communication resource management problem for SCNs to minimize the execution latency of the computation-intensive applications,while two different satellite edge computing scenarios and local execution are considered.Furthermore,the joint computing and communication resource allocation problem for the computation-intensive services is formulated as a mixed-integer programming problem.A game-theoretic and many-to-one matching theorybased scheme(JCCRA-GM)is proposed to achieve an approximate optimal solution.Numerical results show that the proposed method with low complexity can achieve almost the same weight-sum latency as the Brute-force method.

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来源
《中国通信：英文版》 |2021年第7期|236-252|共17页
作者
Shanghong Zhang; Gaofeng Cui; Yating Long; Weidong Wang;
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作者单位

School of Electronic Engineering;

Beijing University of Posts and Telecommunications;

Beijing 100876;

China;

Key Laboratory of Universal Wireless Communications(Beijing University of Posts and Telecommunications);

Beijing 100876;

China;

Science and Technology on Information Transmission and Dissemination in Communication Networks Laboratory;

Hebei 050000;

China;

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原文格式 PDF
正文语种 chi
中图分类 TN9;
关键词
satellite communication networks; edge computing; resource allocation; matching theory;

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1. Mobile Edge Communications,Computing,and Caching(MEC3)Technology in the Maritime Communication Network [J] . Jie Zeng ,Jiaying Sun ,Binwei Wu . 中国通信 . 2020,第005期
2. Multi-Agent Reinforcement Learning for Resource Allocation in IoT Networks with Edge Computing [J] . Xiaolan Liu ,Jiadong Yu ,Zhiyong Feng . 中国通信 . 2020,第009期
3. Resource Allocation in Edge-Computing Based Wireless Networks Based on Differential Game and Feedback Control [J] . Ruijie Lin ,Haitao Xu ,Meng Li . 计算机、材料和连续体(英文) . 2020,第8期
4. Joint Resource Allocation Using Evolutionary Algorithms in Heterogeneous Mobile Cloud Computing Networks [J] . Weiwei Xia ,Lianfeng Shen . 中国通信 . 2018,第008期
5. 网络计算模式(NC,Network Computing)和Java技术 [C] . 王克宏 . 第四届全国计算机应用联合学术会议 . 1997
6. A Radio Resource Allocation Strategy in Future Wireless Communication Systems [A] . ZIRARUSHYA Pierre Celestin . 2008

Joint Computing and Communication Resource Allocation for Satellite Communication Networks with Edge Computing

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