Satellite-Aerial Integrated Computing in Disasters: User Association and Offloading Decision

被引：31

作者：

Zhang, Long ^{[1
]}

Zhang, Hongliang ^{[2
]}

Guo, Chao ^{[4
]}

Xu, Haitao ^{[5
]}

Song, Lingyang ^{[6
]}

Han, Mu ^{[2
,3
]}

机构：

[1] Hebei Univ Engn, Dept Commun Engn, Handan 056038, Peoples R China

[2] Univ Houston, Dept Elect & Comp Engn, Houston, TX 77004 USA

[3] Kyung Hee Univ, Dept Comp Sci & Engn, Seoul 446701, South Korea

[4] Beijing Elect Sci & Technol Inst, Beijing 100070, Peoples R China

[5] Univ Sci & Technol Beijing, Dept Commun Engn, Beijing 100083, Peoples R China

[6] Peking Univ, Dept Elect Engn, Beijing 100871, Peoples R China

来源：

ICC 2020 - 2020 IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS (ICC) | 2020年

关键词：

NETWORKS;

D O I：

10.1109/icc40277.2020.9148796

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

In this paper, a satellite-aerial integrated computing (SAIC) architecture in disasters is proposed, where the computation tasks from two-tier users, i.e., ground/aerial user equipments, are either locally executed at the high-altitude platforms (HAPs), or offloaded to and computed by the Low Earth Orbit (LEO) satellite. With the SAIC architecture, we study the problem of joint two-tier user association and offloading decision aiming at the maximization of the sum rate. The problem is formulated as a 0-1 integer linear programming problem which is NP-complete. A weighted 3-uniform hypergraph model is obtained to solve this problem by capturing the 3D mapping relation for two-tier users, HAPs, and the LEO satellite. Then, a 3D hypergraph matching algorithm using the local search is developed to find a maximum-weight subset of vertex-disjoint hyperedges. Simulation results show that the proposed algorithm has improved the sum rate when compared with the conventional greedy algorithm.

引用

页数：6

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