Towards network convergence and traffic engineering optimization

Faster convergence and optimized traffic engineering are always the pursuits of network operators. However, the link state protocols nowadays have obvious inabilities in achieving these network objectives. In link state network, flooding scheme is usually used to spread the state of link connectivity over the network. Generally, link state flooding introduces various timer configurations for tuning convergence performance. The configuration complexity becomes the major reason of protocol inability to optimize routing convergence. On the other hand, traffic engineering is poorly supported by link state protocol because of temporary status which may cause unexpected traffic migration and packets loss. In this paper, we propose a routing model through which the link state information is disseminated in a globally controllable way. Our model removes existing limitations for accelerating convergence. Meanwhile, our model can integrate traffic engineering into link state protocol by disseminating optimized link weight, thus avoiding the inefficiencies of massive network configurations. Our experiments show that our model can achieve better convergence time and significantly reduce overhead. At the same time, our model is fully scalable with network size. We believe that our model can enhance network convergence and traffic engineering performance simultaneously, as well as prevent unexpected network transitions to improve network reliability.