系统工程与电子技术 ›› 2026, Vol. 48 ›› Issue (11): 4046-4055.doi: 10.12305/j.issn.1001-506X.2026.11.34

• 通信与网络 • 上一篇    下一篇

低轨卫星通信网络的多蚁群协同竞争路由算法

袁新博1(), 徐兆斌1,2, 张大丁1, 成恒飞1, 潘健1, 金仲和1,2,3   

  1. 1. 浙江大学微小卫星研究中心,浙江 杭州 310027
    2. 浙江省微纳卫星研究重点实验室,浙江 杭州 310027
    3. 浣江实验室,浙江 诸暨 311899
  • 收稿日期:2025-09-25 修回日期:2026-02-10 出版日期:2026-10-25 发布日期:2026-06-04
  • 通讯作者: 徐兆斌 E-mail:xinbo@zju.edu.cn
  • 作者简介:袁新博(2000—),男,硕士研究生,主要研究方向为卫星接入与星间路由
    张大丁(2000—),男,博士研究生,主要研究方向为卫星接入与星间路由
    成恒飞(1997—),男,博士研究生,主要研究方向为星间路由
    潘 健(2001—),男,硕士研究生,主要研究方向为卫星通信
    金仲和(1970—),男,教授,博士,主要研究方向为微纳卫星、惯性传感
  • 基金资助:
    国家自然科学基金(U21A20443);国家自然科学基金面上项目(62073289)资助课题

Multi-colony ant cooperative-competitive optimization routing algorithm in low-orbit satellite communication networks

Xinbo Yuan1(), Zhaobin Xu1,2, Dading Zhang1, Hengfei Cheng1, Jian Pan1, Zhonghe Jin1,2,3   

  1. 1. Micro-Satellite Research Center,Zhejiang University,Hangzhou 310027,China
    2. Key Laboratory of Micro-Nano Satellite Research of Zhejiang Province,Hangzhou 310027,China
    3. Huanjiang Laboratory,Zhuji 311899,China
  • Received:2025-09-25 Revised:2026-02-10 Online:2026-10-25 Published:2026-06-04
  • Contact: Zhaobin Xu E-mail:xinbo@zju.edu.cn

摘要:

随着低轨卫星通信网络用户规模不断扩大,其动态拓扑与多业务流竞争导致网络拥塞的问题日益突出。基于此,提出一种多蚁群协同竞争路由算法,旨在提升卫星网络在多源目节点场景下的路由性能。该算法通过建立跨蚁群信息素抑制机制调节蚁群间竞争关系,以引导数据流向负载较低的链路迁移,从而改善链路利用均衡性。基于铱星星座拓扑的仿真表明,该算法能够显著缓解链路资源竞争,降低数据丢包率。在中高负载(0.6~1 Mbps)下,平均端到端时延较传统蚁群算法降低约24.8%;在高业务量场景中,网络吞吐量提升约12.24%。结果表明,所提算法具有良好的拥塞控制与负载均衡能力,适用于动态卫星网络。

关键词: 低轨卫星网络, 启发式路由, 蚁群竞争, 蚁群优化算法, 负载均衡

Abstract:

With the continuous expansion of user scale in low-Earth orbit satellite communication networks, the dynamic topology and multi-service flow competition have led to increasingly prominent network congestion issues. Based on this, a multi-colony ant cooperative-competitive optimization algorithm is proposed to enhance the routing performance of satellite networks in multi-source and multi-destination scenarios. The algorithm regulates the competition relationship among ant colonies by establishing an inter-colony pheromone suppression mechanism, guiding data flows to migrate toward less congested links, thereby improving link utilization balance. Simulations based on the Iridium constellation topology demonstrate that the algorithm significantly alleviates link resource competition and reduces packet loss rate. Under medium to high loads (0.6−1 Mbps), the average end-to-end delay is reduced by approximately 24.8% compared to traditional ant colony algorithms. In high-traffic scenarios, network throughput is improved by approximately 12.24%. The results indicate that the proposed algorithm exhibits effective congestion control and load balancing capabilities, making it suitable for dynamic satellite networks.

Key words: low-orbit satellite network, heuristic routing, ant colony competition, ant colony optimization algorithm, load balancing

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