一种基于时空等级的LEO卫星网络路由策略

doi:10.7527/S1000-6893.2023.27994

Abstract

Abstract:

With the development of 5G technology and the research of 6G technology， the LEO satellite network will play an increasingly important role in the future integrated air-space-ground network. However， the routing strategy as the core technology of the network still faces some challenges， such as high dynamic changes in satellite network topology， frequent switching of paths， limited computing and processing capacity of nodes， and unbalanced load and traffic distribution. Aiming at the problem of unbalanced load in the area covered by the satellite and related to time factors， and the multi-service QoS requirements of users on the satellite， this paper designs a space-time-level-based service classification load balancing routing algorithm. The algorithm considers the relationship between the distribution of satellite network traffic and the space-time level. The satellite node needs to solve its space-time level according to the current moment and the ground area it covers. In the next hop real-time adjustment stage of the routing algorithm， the space-time level is added as one of the routing conditions. At the same time， the calculation method of the threshold is improved， and different link weights are considered when routing to meet the multi-service QoS requirements. The simulation results show that， compared with the DSP algorithm， the TLR algorithm and RMLBR algorithm， although the algorithm in this paper is not as good as the TLR and RMLBR algorithm in terms of total throughput， the delay and ISL utilization have been improved， which effectively reduces the average end-to-end delay， better meets the QoS requirements of different services， and balances the network load.

Key words: LEO satellite network, load balance, QoS, routing algorithm, space-time factors

CLC Number:

V474.2

Debin WEI, Yu CAO, Li YANG, Chengsheng PAN. A routing strategy for LEO satellite network based on space⁃time⁃level[J]. Acta Aeronautica et Astronautica Sinica, 2023, 44(16): 327994-327994.

Figures/Tables 14

Fig.1

Fig.2

Fig.3

Table 1

Correspondence between the current and next⁃hop cache queue occupation and Ss

$Q O R c$	$T Q O R n$	$S s$
$0, δ 1$	$0, τ 1$	Free
$δ 1, δ 2$	$τ 1, τ 2$	Busy
$δ 2, 1$	$τ 2, 1$	Congested

Table 1

Table2

Combine L and S traffic light color setting

$L$ 逻辑关系	$S$ 逻辑关系	交通灯颜色
$L s ≥ L n$	$S s = F r e e & S n = F r e e$	绿
	Otherwise	黄
	$S s = C o n g e s t e d o r S n = C o n g e s t e d$	红
$L s < L n$	$S s = F r e e & S n = F r e e$	黄
$L s < L n$	Otherwise	红

Table2

Table 3

Traffic light color next⁃hop node selection rules in different directions

$H o p t i m a l$ 方向交通灯颜色	$H s u b o p t i m a l$ 方向交通灯颜色	下一跳选择
绿色	任何颜色	$H o p t i m a l$
黄色	绿色/黄色	一半发 $H o p t i m a l$ ，一半发 $H s u b o p t i m a l$
黄色	红色	$H o p t i m a l$
红色	绿色/黄色	$H s u b o p t i m a l$
红色	红色	公共等待队列

Table 3

Table 4

Table 5

Fig.4

Fig.5

Fig.6

Fig.7

Fig.8

Fig.9

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参数	数值
轨道高度/km	780
轨道平面个数	6
每个平面中卫星个数	11
轨道倾斜角度/（°）	86.4
极地地区的纬度阈值/（°）	60
ISL带宽/Mbps	25
数据包分组大小/KBytes	1
缓冲队列数据包大小/个	100
全局路由信息更新间隔/ms	600

源	目的
源	亚洲	欧洲	非洲	北美洲	南美洲	大洋洲
亚洲	50	10	2	30	2	6
欧洲	10	40	2	40	5	3
非洲	5	30	20	40	2	3
北美洲	10	15	2	60	10	3
南美洲	8	12	2	35	40	3
大洋洲	12	10	2	40	2	34

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A routing strategy for LEO satellite network based on space⁃time⁃level

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