中国电子科技集团有限公司电子科学研究院,北京 100041
[ "周欣(2001- ),女,中国电子科技集团有限公司电子科学研究院硕士生,主要研究方向为卫星通信网络。" ]
[ "丁文慧(1987- ),女,中国电子科技集团有限公司电子科学研究院高级工程师,主要研究方向为卫星通信网络。" ]
[ "丁春旭(1998- ),男,中国电子科技集团有限公司电子科学研究院助理工程师,主要研究方向为卫星通信系统仿真、卫星通信网络路由。" ]
[ "成俊峰(1991- ),女,中国电子科技集团有限公司电子科学研究院工程师,主要研究方向为卫星通信网络。" ]
[ "陆洲(1970- ),男,中国电子科技集团有限公司电子科学研究院研究员,主要研究方向为卫星通信网络。" ]
收稿:2025-07-14,
修回:2025-09-17,
纸质出版:2025-12-20
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周欣,丁文慧,丁春旭等.基于蚁群优化的软件定义低轨卫星网络流量负载均衡算法[J].天地一体化信息网络,2025,06(04):59-71.
ZHOU Xin,DING Wenhui,DING Chunxu,et al.Ant Colony Optimization-Based Traffic Load Balancing Algorithm for Software Defined Low Earth Orbit Satellite Networks[J].Space-Integrated-Ground Information Networks,2025,06(04):59-71.
周欣,丁文慧,丁春旭等.基于蚁群优化的软件定义低轨卫星网络流量负载均衡算法[J].天地一体化信息网络,2025,06(04):59-71. DOI: 10.11959/j.issn.1000-0801.2025039.
ZHOU Xin,DING Wenhui,DING Chunxu,et al.Ant Colony Optimization-Based Traffic Load Balancing Algorithm for Software Defined Low Earth Orbit Satellite Networks[J].Space-Integrated-Ground Information Networks,2025,06(04):59-71. DOI: 10.11959/j.issn.1000-0801.2025039.
针对当前低轨卫星网络链路资源利用不均衡和业务服务质量(quality of service,QoS)难以得到保障的问题,提出一种蚁群优化的软件定义低轨卫星网络流量负载均衡算法,即动态负载均衡蚁群算法。该算法通过软件定义网络架构获取卫星网络实时链路信息,根据业务QoS需求设计综合路径权重参数,基于当前链路状态优化蚁群算法的信息素更新规则,实时更新蚁群算法的信息素,基于优化后的信息素和转移概率计算卫星网络最优路径,并下发至各卫星节点。仿真实验在局部轻载、局部中等负载、局部拥塞3种流量场景和不同低轨卫星星座规模下进行,将该算法与迪杰斯特拉算法和蚁群算法进行对比验证。结果表明,该算法在满足业务服务质量、避免网络拥塞的同时,显著提高了低轨卫星网络的负载均衡能力。
In order to solve the problem of unbalanced link resource utilization and difficult quality of service guarantee in current low earth orbit satellite networks
a software-defined low earth orbit satellite network traffic load balancing algorithm based on ant colony optimization
namely dynamic load balancing ant colony algorithm
is proposed. This algorithm acquires real-time link information of the satellite network through the software defined network architecture
designs comprehensive path weight parameters according to the QoS requirements of the service
optimizes the pheromone update rules of the ant colony algorithm based on the current link states
updates the pheromones of the ant colony algorithm in real time
calculates the optimal path of the satellite network based on the optimized pheromones and transition probabilities
and sends it to each satellite node. Simulation experiments are conducted under three traffic scenarios of local light load
local medium load and local congestion
and under different scales of low earth orbit satellite constellation scales
this algorithm was compared with Dijkstra optimization and ant colony algorithm. The results show that this algorithm significantly improves the load balancing capability of low earth orbit satellite networks while meeting the quality of service requirements and avoiding network congestion.
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