A Game-Theoretical Approach for Distributed Computation Offloading in LEO Satellite-Terrestrial Edge Computing Systems

被引:0
作者
Chen, Ying [1 ]
Yang, Yaozong [1 ]
Hu, Jintao
Wu, Yuan [2 ]
Huang, Jiwei [3 ,4 ]
机构
[1] Beijing Informat Sci & Technol Univ, Sch Comp Sci, Beijing 100101, Peoples R China
[2] Univ Macau, State Key Lab Internet Things Smart City, Macau 999078, Peoples R China
[3] China Univ Petr, Hainan Inst, Beijing 102249, Peoples R China
[4] China Univ Petr, Beijing Key Lab Petr Data Min, Beijing 102249, Peoples R China
基金
北京市自然科学基金; 中国国家自然科学基金;
关键词
Low earth orbit satellites; Satellites; Edge computing; Costs; Space-air-ground integrated networks; Servers; Delays; Cloud computing; Base stations; Nash equilibrium; Low earth orbit (LEO) satellite-terrestrial edge computing; game theory; Nash equilibrium (NE); computation offloading; RESOURCE-ALLOCATION; NETWORKS;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Due to the limitations of computing resources and battery capacity, the computation tasks of ground devices can be offloaded to edge servers for processing. Moreover, with the development of the low earth orbit (LEO) satellite technology, LEO satellite-terrestrial edge computing can realize a global coverage network to provide seamless computing services beyond the regional restrictions compared to the conventional terrestrial edge computing networks. In this paper, we study the computation offloading problem in the LEO satellite-terrestrial edge computing systems. Ground devices can offload their computation tasks to terrestrial base stations (BSs) or LEO satellites deployed on edge servers for remote processing. We formulate the computation offloading problem to minimize the cost of devices while satisfying resource and LEO satellite communication time constraints. Since each ground device competes for transmission and computing resources to reduce its own offloading cost, we reformulate this problem as the LEO satellite-terrestrial computation offloading game (LSTCO-Game). It is derived that there is an upper bound on transmission interference and computing resource competition among devices. Then, we theoretically prove that at least one Nash equilibrium (NE) offloading strategy exists in the LSTCO-Game. We propose the game-theoretical distributed computation offloading (GDCO) algorithm to find the NE offloading strategy. Next, we analyze the cost obtained by GDCO's NE offloading strategy in the worst case. Experiments are conducted by comparing the proposed GDCO algorithm with other computation offloading methods. The results show that the GDCO algorithm can effectively reduce the offloading cost.
引用
收藏
页码:4389 / 4402
页数:14
相关论文
共 43 条
[31]   Hybrid Centralized and Distributed Learning for MEC-Equipped Satellite 6G Networks [J].
Rodrigues, Tiago Koketsu ;
Kato, Nei .
IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, 2023, 41 (04) :1201-1211
[32]   Energy-Efficient Multiaccess Edge Computing for Terrestrial-Satellite Internet of Things [J].
Song, Zhengyu ;
Hao, Yuanyuan ;
Liu, Yuanwei ;
Sun, Xin .
IEEE INTERNET OF THINGS JOURNAL, 2021, 8 (18) :14202-14218
[33]   Computation Offloading in LEO Satellite Networks With Hybrid Cloud and Edge Computing [J].
Tang, Qingqing ;
Fei, Zesong ;
Li, Bin ;
Han, Zhu .
IEEE INTERNET OF THINGS JOURNAL, 2021, 8 (11) :9164-9176
[34]   Joint Task Offloading and Resource Allocation for Multi-Server Mobile-Edge Computing Networks [J].
Tran, Tuyen X. ;
Pompili, Dario .
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2019, 68 (01) :856-868
[35]  
Wang YJ, 2018, PROCEEDINGS OF 2018 IEEE INTERNATIONAL CONFERENCE ON COMMUNICATION SYSTEMS (ICCS 2018), P450, DOI 10.1109/ICCS.2018.8689224
[36]   Joint Computation Offloading, Role, and Location Selection in Hierarchical Multicoalition UAV MEC Networks: A Stackelberg Game Learning Approach [J].
Wu, Qihui ;
Chen, Jiaxin ;
Xu, Yuhua ;
Qi, Nan ;
Fang, Tao ;
Sun, Youming ;
Jia, Luliang .
IEEE INTERNET OF THINGS JOURNAL, 2022, 9 (19) :18293-18304
[37]   Satellite-Terrestrial Integrated Edge Computing Networks: Architecture, Challenges, and Open Issues [J].
Xie, Renchao ;
Tang, Qinqin ;
Wang, Qiuning ;
Liu, Xu ;
Yu, F. Richard ;
Huang, Tao .
IEEE NETWORK, 2020, 34 (03) :224-231
[38]   Carbon-Aware Dynamic Task Offloading in NOMA-Enabled Mobile Edge Computing for IoT [J].
Yang, Yaozong ;
Chen, Ying ;
Li, Kaixin ;
Huang, Jiwei .
IEEE INTERNET OF THINGS JOURNAL, 2024, 11 (09) :15723-15734
[39]   Satellite Edge Computing With Collaborative Computation Offloading: An Intelligent Deep Deterministic Policy Gradient Approach [J].
Zhang, Hangyu ;
Liu, Rongke ;
Kaushik, Aryan ;
Gao, Xiangqiang .
IEEE INTERNET OF THINGS JOURNAL, 2023, 10 (10) :9092-9107
[40]   Task Offloading in Vehicular Edge Computing Networks: A Load-Balancing Solution [J].
Zhang, Jie ;
Guo, Hongzhi ;
Liu, Jiajia ;
Zhang, Yanning .
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2020, 69 (02) :2092-2104