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ACTA AERONAUTICAET ASTRONAUTICA SINICA ›› 2023, Vol. 44 ›› Issue (1): 326422-326422.doi: 10.7527/S10006893.2021.26422

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Multi-QoS constraints routing algorithm based on satellite network dynamic resource graph

Chao LIANG1, Li YANG2(), Chengsheng PAN1,2, Yaowen QI2   

  1. 1.Communication and Networks Laboratory,Dalian University,Dalian  116622,China
    2.School of Automation,Nanjing University of Science and Technology,Nanjing  210094,China
  • Received:2021-09-22 Revised:2021-11-18 Accepted:2021-11-24 Online:2023-01-15 Published:2021-12-06
  • Contact: Li YANG E-mail:yangli945@126.com
  • Supported by:
    National Natural Science Foundation of China(61931004)

Abstract:

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.

Key words: satellite network, Software Defined Network (SDN), dynamic resource graph, multi-objective optimization, ant colony algorithm

CLC Number: