Service Function Chain Deployment Algorithm Based on Deep Reinforcement Learning in Space-Air-Ground Integrated Network

被引:3
作者
Feng, Xu [1 ]
He, Mengyang [1 ,2 ]
Zhuang, Lei [3 ]
Song, Yanrui [3 ]
Peng, Rumeng [1 ]
机构
[1] Zhengzhou Univ, Sch Cyber Sci & Engn, Zhengzhou 450000, Peoples R China
[2] Song Shan Lab, Zhengzhou 450000, Peoples R China
[3] Zhengzhou Univ, Sch Comp & Artificial Intelligence, Zhengzhou 450000, Peoples R China
关键词
space-air-ground integrated network; DRL; resource allocation; NFV; ORCHESTRATION; INTERNET;
D O I
10.3390/fi16010027
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
SAGIN is formed by the fusion of ground networks and aircraft networks. It breaks through the limitation of communication, which cannot cover the whole world, bringing new opportunities for network communication in remote areas. However, many heterogeneous devices in SAGIN pose significant challenges in terms of end-to-end resource management, and the limited regional heterogeneous resources also threaten the QoS for users. In this regard, this paper proposes a hierarchical resource management structure for SAGIN, named SAGIN-MEC, based on a SDN, NFV, and MEC, aiming to facilitate the systematic management of heterogeneous network resources. Furthermore, to minimize the operator deployment costs while ensuring the QoS, this paper formulates a resource scheduling optimization model tailored to SAGIN scenarios to minimize energy consumption. Additionally, we propose a deployment algorithm, named DRL-G, which is based on heuristics and DRL, aiming to allocate heterogeneous network resources within SAGIN effectively. Experimental results showed that SAGIN-MEC can reduce the end-to-end delay by 6-15 ms compared to the terrestrial edge network, and compared to other algorithms, the DRL-G algorithm can improve the service request reception rate by up to 20%. In terms of energy consumption, it reduces the average energy consumption by 4.4% compared to the PG algorithm.
引用
收藏
页数:20
相关论文
共 34 条
[1]   Dynamic Topology Design of NFV-Enabled Services Using Deep Reinforcement Learning [J].
Alhussein, Omar ;
Zhuang, Weihua .
IEEE TRANSACTIONS ON COGNITIVE COMMUNICATIONS AND NETWORKING, 2022, 8 (02) :1228-1238
[2]   Data Aggregation in UAV-Aided Random Access for Internet of Vehicles [J].
Bai, Lin ;
Liu, Jiexun ;
Wang, Jiaxing ;
Han, Rui ;
Choi, Jinho .
IEEE INTERNET OF THINGS JOURNAL, 2022, 9 (08) :5755-5764
[3]   A first Fit type algorithm for the coupled task scheduling problem with unit execution time and two exact delays [J].
Bekesi, Jozsef ;
Dosa, Gyorgy ;
Galambos, Gabor .
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2022, 297 (03) :844-852
[4]   Edge-Cloud Resource Scheduling in Space-Air-Ground-Integrated Networks for Internet of Vehicles [J].
Cao, Bin ;
Zhang, Jintong ;
Liu, Xin ;
Sun, Zhiheng ;
Cao, Wenxi ;
Nowak, Robert M. ;
Lv, Zhihan .
IEEE INTERNET OF THINGS JOURNAL, 2022, 9 (08) :5765-5772
[5]   HAP-Reserved Communications in Space-Air-Ground Integrated Networks [J].
Cao, Xuelin ;
Yang, Bo ;
Yuen, Chau ;
Han, Zhu .
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2021, 70 (08) :8286-8291
[6]   Hierarchical Domain-Based Multicontroller Deployment Strategy in SDN-Enabled Space-Air-Ground Integrated Network [J].
Chen, Chen ;
Liao, Zhan ;
Ju, Ying ;
He, Ci ;
Yu, Keping ;
Wan, Shaohua .
IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS, 2022, 58 (06) :4864-4879
[7]   Effect of Intelligent Multi-Association in Civil Aircraft-Augmented SAGIN [J].
Chen, Qian ;
Meng, Weixiao ;
Han, Shuai ;
Li, Cheng ;
Chen, Hsiao Hwa .
IEEE TRANSACTIONS ON COGNITIVE COMMUNICATIONS AND NETWORKING, 2023, 9 (01) :223-238
[8]   Civil Aircrafts Augmented Space-Air-Ground-Integrated Vehicular Networks: Motivation, Breakthrough, and Challenges [J].
Chen, Qian ;
Meng, Weixiao ;
Li, Shuxun ;
Li, Cheng ;
Chen, Hsiao-Hwa .
IEEE INTERNET OF THINGS JOURNAL, 2022, 9 (08) :5670-5683
[9]   6G service-oriented space-air-ground integrated network: A survey [J].
Cheng, Nan ;
He, Jingchao ;
Yin, Zhisheng ;
Zhou, Conghao ;
Wu, Huaqing ;
Lyu, Feng ;
Zhou, Haibo ;
Shen, Xuemin .
CHINESE JOURNAL OF AERONAUTICS, 2022, 35 (09) :1-18
[10]   A Survey on Distributed NFV Multi-Domain Orchestration from an Algorithmic Functional Perspective [J].
Cisneros, Josue Castaneda ;
Yangui, Sami ;
Hernandez, Saul E. Pomares ;
Drira, Khalil .
IEEE COMMUNICATIONS MAGAZINE, 2022, 60 (08) :60-65