A Load Balancing Routing Strategy for LEO Satellite Network

Liu, Jiang; Luo, Ruizhi; Huang, Tao; Meng, Chunwei

doi:10.1109/access.2020.3017615

Cited by 38 publications

(17 citation statements)

References 11 publications

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“…proposed a load balancing routing scheme by hybrid-traffic-detour [ 24 ]. They calculated and designed the shortest path and a long-distance traffic detour path to forward packets and determine which path to use for forwarding to against link congestion [ 25 ]. The scheme tried to avoid a situation in which the routing path between a node and its neighbors were directed toward the same destination node.…”

Section: Related Workmentioning

confidence: 99%

A Novel Load Balancing Scheme for Satellite IoT Networks Based on Spatial–Temporal Distribution of Users and Advanced Genetic Algorithms

Lin

Dong

Wang

et al. 2022

Sensors

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Satellite IoT networks (S-IoT-N), which have been a hot issue regarding the next generation of communication, are quite important for the coming era of digital twins and the metaverse because of their performance in sensing and monitoring anywhere, anytime, and anyway, in more dimensions. However, this will cause communication links to face greater traffic loads. Satellite internet networks (SIN) are considered the most possible evolution road, possessing characteristics of many satellites, such as low earth orbit (LEO), the Ku/Ka frequency, and a high data rate. Existing research on load balancing schemes for satellite networks cannot solve the problems of low efficiency under conditions of extremely non-uniform distribution of users (DoU) and dynamic density variances. Therefore, this paper proposes a novel load balancing scheme of adjacent beams for S-IoT-N based on the modeling of spatial–temporal DoU and advanced GA. In our scheme, the PDF of the DoU in the direction of movement of the SSP’s trajectory was modeled first, which provided a multi-directional constraint for the non-uniform distribution of users in S-IoT-N. Fully considering the prior periodicity of satellite movement and the similarity of DoU in different areas, we proposed an adaptive inheritance iteration to optimize the crossover factor and mutation factor for GA for the first time. Based on the proposed improved GA, we obtained the optimal scheme of load balancing under the conditions of the adaptation from the local balancing scheme to global balancing, and a selection of Ser-Beams to access. Finally, the simulations show that the proposed method can improve the average throughput by 3% under specific conditions and improve processing efficiency by 30% on average.

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Section: Related Workmentioning

confidence: 99%

A Novel Load Balancing Scheme for Satellite IoT Networks Based on Spatial–Temporal Distribution of Users and Advanced Genetic Algorithms

Lin

Dong

Wang

et al. 2022

Sensors

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“…In TLR, the ISL congestion is predicted to re-calculate routing. Another proactive distributed routing method is the selective split load balancing strategy (SSLB) [ 26 ], in which the traffic flow of congestion nodes is diverted to neighboring nodes. However, all ISLs are assumed to have equal length, it can hardly reflect the time-varying feature of propagation delay in real satellite networks.…”

Section: Related Workmentioning

confidence: 99%

“…Meanwhile, packet delay, throughput and packet drop rate are adopted as the performance metrics. In the experiments, the proposed TSR algorithm is compared with the Dijkstra Shortest-Path (DSP) [ 23 ], Traffic-Light-based Routing (TLR) [ 25 ], Netgrid-based Shortest path Routing (NSR) [ 21 ] and Selective Split Load Balancing routing Strategy (SSLB) [ 26 ]. Specifically, DSP adopts the gathered global propagation delay to find the optimal routing path, TLR is a load balancing routing scheme, which considers local route adjustment, NSR utilizes static cubes to find the shortest distance path, and SSLB is a distributed strategy, which diverts the traffic flow of congestion nodes to neighboring nodes.…”

Section: Simulation and Analysismentioning

confidence: 99%

Link-State Aware Hybrid Routing in the Terrestrial–Satellite Integrated Network

Shi

Liu

et al. 2022

Sensors

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In this paper, we study data transmission in the Terrestrial–Satellite Integrated Network (TSIN), where terrestrial networks and satellites are combined together to provide seamless global network services for ground users. However, efficiency of the data transmission is limited by the time-varying inter-satellite link connection and intermittent terrestrial–satellite link connection. Therefore, we propose a link-state aware hybrid routing algorithm, which selects the integrated data transmission path adaptively in this paper. First of all, a space–time topology model is constructed to represent the dynamic link connections in TSIN. Thus, the transmission delay can be analyzed accordingly, and the data transmission problem can then be formulated. To balance the effectiveness and accuracy of searching a hybrid path, we carefully discuss the optimization of space–time topology updating, and propose an inter-satellite link selection algorithm. For the terrestrial–satellite link in hybrid routing, the data transmission problem is transformed into a weighted bipartite graph matching problem and solved with a Kuhn–Munkres-based link selection algorithm. To verify the effectiveness of our proposed routing algorithm, extensive simulations are conducted based on a realistic Hongyun constellation project. Results show that the network performance is improved with respect to data transmission delay, packet loss rate, and throughput.

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“…These multiple paths cause route oscillations, generated by the memoryless nature of the Dijkstra's algorithm. The proposed algorithm stores some candidates for the next hop from the previously generated routing table . Liu et al [27] propose a selective iterative Dijkstra algorithm, which changes the order in which nodes are traversed (as in classic Dijkstra's), so that the load in the network is distributed fairly. Then, to reduce congestion, the authors propose Selective Shunt Load Balancing (SSLB), which is a distributed congestion control algorithm, using the traffic flow as an estimate of congestion in a part of the network.…”

Section: Related Workmentioning

confidence: 99%

Distributed Probabilistic Congestion Control in LEO Satellite Networks

Page¹,

Bhargao²,

V.³

et al. 2022

Preprint

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Satellite communication in Low Earth Orbiting (LEO) constellations is an emerging topic of interest. Due to the high number of LEO satellites in a typical constellation, a centralized algorithm for minimum-delay packet routing would incur significant signaling and computational overhead. We can exploit the deterministic topology of the satellite constellation to calculate the minimum-delay path between any two nodes in the satellite network. But that does not take into account the traffic information at the nodes along this minimum-delay path. We propose a distributed probabilistic congestion control scheme to minimize end-to-end delay. In the proposed scheme, each satellite, while sending a packet to its neighbor, adds a header with a simple metric indicating its own congestion level. The decision to route packets is taken based on the latest traffic information received from the neighbors We build this algorithm onto the Datagram Routing Algorithm (DRA), which provides the minimum delay path, and the decision for the next hop is taken by the congestion control algorithm. We compare the proposed congestion control mechanism with the existing congestion control used by the DRA via simulations, and show improvements over the same.

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A Load Balancing Routing Strategy for LEO Satellite Network

Cited by 38 publications

References 11 publications

A Novel Load Balancing Scheme for Satellite IoT Networks Based on Spatial–Temporal Distribution of Users and Advanced Genetic Algorithms

A Novel Load Balancing Scheme for Satellite IoT Networks Based on Spatial–Temporal Distribution of Users and Advanced Genetic Algorithms

Link-State Aware Hybrid Routing in the Terrestrial–Satellite Integrated Network

Distributed Probabilistic Congestion Control in LEO Satellite Networks

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