Optimization of OSPF Weights Using On-line Simulation

In this paper, we present an OSPF weights optimization scheme using a general automatic network management framework proposed in [1], i.e., on-line simulation framework. We have chosen the packet drop rate in the network as the optimization metric as it is a good indicator of congestion in the network and also impacts the performance of the underlying applications. The packet drop rate has been formulated in terms of the link parameters, such as bandwidth and buffer space, and the parameters of the traffic demands. A GI/M/1/K queuing model has been used to compute the packet drop probability on a given link. We have also developed a fast recursive random search algorithm to address the issues associated with network optimization problems. The search algorithm has been compared to the local search heuristic of [4] in terms of the number of function evaluations needed to obtain a “good” OSPF link weight setting. Our results demonstrate that the recursive random search takes 50-90% fewer function evaluations to find a “good” setting. The amount of improvement depends on the network topology, traffic conditions and optimization metric. We have simulated the proposed OSPF optimization scheme in ns[19] and the results indicated improvements of the order of 30-60% in the total packet drop rate. Index Terms Traffic Engineering, OSPF, Optimization 2