Routing optimization method for multi-domain traffic engineering in distributed software-defined networking
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1.a. School of Computer Science and Software Engineering, Southwest Petroleum University, Chengdu 610500, P. R. China; 1b. Data Mining and Knowledge Management Key Laboratory of Nanchong City, Southwest Petroleum University, Nanchong, Sichuan 637001, P. R. China; 2. College of Computer Science, Sichuan University, Chengdu 610065, P. R. China

Clc Number:

TP393

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Supported by National Natural Science Foundation of China (61373091), and the Science & Technology Program of Nanchong, China (19SXHZ0012).

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    Abstract:

    Addressing the challenge of unbalanced traffic management and scheduling in distributed software-defined networking (SDN) for traffic engineering, we propose a solution for traffic routing optimization across multi-control domains based on load balancing. Firstly, we define the composition of message traffic and the rules for intra-domain and inter-domain communication. Then, we establish an optimization model aiming at balancing controller loads and minimizing maximum link utilization. The model is based on the composition of control link traffic using four control messages, with link traffic divided into control message traffic and network traffic. Finally, we propose a two-layer routing algorithm based on communication rules. To improve the accuracy of the model solution, we introduce an improved discrete firefly algorithm. Evaluating the model using the ABILENE network and GEANT network, we assess indicators such as control message traffic, controller load, and link load. Experimental results show that the optimization model effectively balances loads between controllers and links, emphasizing the significance of managing message traffic in traffic engineering. Compared to centralized control modes, the average controller load in the flat distributed control mode is reduced by 47.3%, with the the maximum link utilization difference not exceeding 15%.

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王坤,吕光宏,胥林,杨晗,邓慧.分布式软件定义网络中多域流量工程的路由优化方法[J].重庆大学学报,2024,47(7):110~124

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History
  • Received:August 22,2022
  • Revised:
  • Adopted:
  • Online: August 15,2024
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