A load balanced routing algorithm based on congestion prediction for LEO satellite networks

Wang, Houtian; Wen, Guoli; Liu, Naijin; Zhang, Jun; Tao, Ying

doi:10.1007/s10586-017-1579-8

Cited by 10 publications

(14 citation statements)

References 12 publications

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“…The new objective function established in this paper is a complex optimization problem, which makes it difficult to perform online computing. Reference [30] verified that the ant colony algorithm has some advantages in solving such functions, but the pheromone transfer and updating method has a slow convergence speed and easily falls to the local optimal path, making it unsuitable for the conflict benefit model proposed in this paper. Therefore, KFWCA is designed to find the optimal solution, thus guaranteeing the reliability and robustness of complex multidimensional and multipeak functions.…”

Section: ( )mentioning

confidence: 99%

“…With the continuous improvements in the routing strategies of ground-based wireless networks, intelligent optimization algorithms such as the bee colony algorithm, ant colony algorithm and particle swarm algorithm have been extended to topological optimization and routing decision making for satellite networks in recent years [8][9][10]. Reference [30] verified the application value of the ant colony algorithm in single-layer NGEO. The algorithm aims to determine the shunting probability of the next routing node through the superposition and release of pheromones.…”

Section: Related Workmentioning

confidence: 99%

“…The monitoring interval of the queue is set to 10 ms, the Kalman measurement noise 2 Q= packets, According to the data in reference [15], a global traffic flow table is established, and the traffic flow over the course of a day is 1.6 Tb; the average value over 10 repetitions for 24 hours is the experimental result. In this paper, the Dijkstra, TLR [26], and LBPRA-CP [30] algorithms are compared with the KFWCA. The route update time of each algorithm is 40 s. A route optimization strategy based on ant pheromones was proposed in the literature [30].…”

Section: A Experimental Parameter Configurationmentioning

confidence: 99%

“…In this paper, the Dijkstra, TLR [26], and LBPRA-CP [30] algorithms are compared with the KFWCA. The route update time of each algorithm is 40 s. A route optimization strategy based on ant pheromones was proposed in the literature [30]. The algorithm continuously adjusts the probability of each node through forward and reverse ant movements and finally completes the route table update based on load balancing.…”

Section: A Experimental Parameter Configurationmentioning

confidence: 99%

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A Routing Model Based on Multiple-User Requirements and the Optimal Solution

Liu

Zhang

2020

IEEE Access

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To promote the development of high-bandwidth IP networks of nongeostationary Earth orbit (NGEO) satellites, this paper designs a new benefit measurement model. Moreover, we propose the class-A QoS benefit criterion (QABC), which is established based on a mathematical model involving the remaining queue length and QoS. The benefit model includes three maximum and minimum conflict subgoals and is designed to avoid the problem that the ant colony algorithm easily falls to local optima. This new model is solved with the wolf colony algorithm, which provides both next-hop selection and bottleneck bandwidth reservation mechanisms. Additionally, many burst flows can occur in satellite networks, and they lead to a slow convergence speed and unnecessary overhead. In this paper, the Kalman filter algorithm is used to address these issues. Considering the long-term correlation of satellite traffic, it is feasible to smooth the queue length with a Kalman filter. Finally, the Kalman filter wolf colony algorithm (KFWCA) can solve the conflict problem in the new benefit measurement model. The algorithm is applied in the network simulator NS2.35, and the results verify the effectiveness of load balancing and QoS maximization in a satellite network. The results indicate that the KFWCA yields better performance than other algorithms based on traffic allocation, the average delay, the packet loss rate and other factors, especially under high-traffic conditions. INDEX TERMS benefit measurement model; KFWCA; QoS support; load balancing I. INTRODUCTION

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Section: ( )mentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: A Experimental Parameter Configurationmentioning

confidence: 99%

Section: A Experimental Parameter Configurationmentioning

confidence: 99%

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A Routing Model Based on Multiple-User Requirements and the Optimal Solution

Liu

Zhang

2020

IEEE Access

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“…In contrast, distributed load balancing schemes can provide fast reaction to traffic changes [12][13][14][15][16][17]. In such category, the ant colony algorithm is a class of simulated evolutionary algorithms good at finding the optimal path under dynamic network environments [18]. Therefore, in this paper, we aim at the traffic imbalance problem in LEO satellite networks and propose an ant colony optimization routing algorithm with window reduction (ACORA-WR).…”

Section: Introductionmentioning

confidence: 99%

An Ant Colony Optimization-Based Routing Algorithm for Load Balancing in LEO Satellite Networks

Deng

Zeng

Chang

et al. 2022

Wireless Communications and Mobile Computing

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Satellite networks can provide a wider service range and lower delay than traditional terrestrial optical fiber networks. However, due to the bursty characteristic of the Internet traffic and the distributive feature of satellite links, traffic-intensive areas often suffer from link congestion while links in other areas are underutilized, i.e., the traffic imbalance problem in LEO satellite networks. In this paper, an ant colony optimization routing algorithm with window reduction for LEO satellite networks, ACORA-WR, is proposed to achieve load balancing. ACORA-WR limits the movement of the ant colony to a specific range and comprehensively considers the path distance, transmission direction, and link load to find a path with low delay and overhead. Simulation results verify that the proposed ACORA-WR scheme demonstrates high data delivery ratio and network throughput, while ensuring low average delay and network transmission overhead.

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Software defined network‐based multipath state‐aware routing with traffic prediction in satellite network

Luo,

Ning,

Chen

et al. 2023

Trans Emerging Tel Tech

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Uneven traffic demand in satellite networks can lead to link congestion and influence network communication quality. To tackle this problem, we propose a state‐aware routing algorithm based on traffic prediction to disperse network traffic. Reducing the onboard processing requirements, the routing algorithm in this paper introduces a software‐defined network to decouple the control plane and data plane of the satellite network. Also, to better sense the trend of network state, the routing algorithm devises a Spatial‐Temporal Attention Fusion Graph Neural Network (STAFGNN) to predict the future network state by capturing the spatial‐temporal correlation of satellite network traffic. In the control plane, the routing algorithm senses the network state by predicting the future satellite traffic and aggregates the real‐time states of neighboring satellites to identify the load level of the zone. The data plane forwards data based on the control information. Based on the routing algorithm in this paper, multipath routing is designed to reduce the probability of link congestion by dispersing each end‐to‐end traffic. The simulation results demonstrate that the routing algorithm in this paper reduces the number of congestion links and balances the load distribution. The proposed algorithm provides an idea to introduce deep learning to solve the load balancing problem in satellite networks.

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A load balanced routing algorithm based on congestion prediction for LEO satellite networks

Cited by 10 publications

References 12 publications

A Routing Model Based on Multiple-User Requirements and the Optimal Solution

A Routing Model Based on Multiple-User Requirements and the Optimal Solution

An Ant Colony Optimization-Based Routing Algorithm for Load Balancing in LEO Satellite Networks

Software defined network‐based multipath state‐aware routing with traffic prediction in satellite network

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