卫星网络动态资源图多QoS约束路由算法
收稿日期: 2021-09-22
修回日期: 2021-11-18
录用日期: 2021-11-24
网络出版日期: 2021-12-06
基金资助
国家自然科学基金(61931004)
Multi-QoS constraints routing algorithm based on satellite network dynamic resource graph
Received date: 2021-09-22
Revised date: 2021-11-18
Accepted date: 2021-11-24
Online published: 2021-12-06
Supported by
National Natural Science Foundation of China(61931004)
针对高动态卫星网络拓扑变化导致的网络更新期间可用路径失效，QoS需求难以满足的问题，提出了一种基于软件定义网络（SDN）架构的虚拟节点动态资源图多QoS约束路由算法（DRGVN-QR）。根据节点的切换状态、缓存以及链路的剩余带宽、时延等信息，结合虚拟节点的网络拓扑方式，建立虚拟节点动态资源图模型。根据资源图模型，建立最小路径代价的优化模型，利用蚁群算法（ACO）并发地为每个连接请求找到一段时间范围内的最优路径集合，并对信息素挥发系数的取值问题进行了讨论，以提升路径质量和算法性能。最后，为了适应卫星网络的时变性，设计一种幂数加权公式求出一段时间范围内的最优路径。仿真结果表明：DRGVN-QR算法能够规避路径失效带来的传输中断问题，提高网络QoS，与其他算法相比，该算法降低了平均端到端时延、网络丢包率和时延抖动。
关键词： 卫星网络; 软件定义网络（SDN）; 动态资源图; 多目标优化; 蚁群算法
梁超 , 杨力 , 潘成胜 , 戚耀文 . 卫星网络动态资源图多QoS约束路由算法[J]. 航空学报, 2023 , 44(1) : 326422 -326422 . DOI: 10.7527/S10006893.2021.26422
To address the problems of available path failure during network update caused by topology change of high dynamic satellite network and difficulty in meeting QoS requirements， a Dynamic Resource Graph of Virtual Node multi-QoS constraint Routing algorithm （DRGVN-QR） is proposed based on the SDN architecture. According to the information including switching state， cache of the nodes and remaining bandwidth， and delay of the link， as well as the network topology of the virtual node， a dynamic resource graph model of the virtual node is established. According to the resource graph model， an optimization model of the minimum path cost is established. The Ant Colony Algorithm （ACO） is used to concurrently find the optimal path set within a period of time for each connection request， and the value of the pheromone volatilization coefficient is discussed to improve the path quality and algorithm performance. Finally， to adapt to the time variability of satellite networks， an idempotent weighting formula is designed to find the optimal path in a period of time. Simulation results show that the algorithm proposed can avoid the transmission interruption caused by path failure， and improve the QoS of network. Compared with other algorithms， this algorithm reduces the average end-to-end delay， network packet loss rate and delay jitter.
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