This paper proposes a Preventive Start-time Optimization with no penalty (PSO-NP). PSO-NP determines a suitable set of Open Shortest Path First (OSPF) link weights at the network operation start time that can handle any link failure scenario preventively while considering both failure and non failure scenarios. Preventive Start-time Optimization (PSO) was designed to minimize the worst case congestion ratio (maximum link utilization over all the links in the network) in case of link failure. PSO considers all failure patterns to determine a link weight set that counters the worst case failure. Unfortunately, when there is no link failure, that link weight set leads to a higher congestion ratio than that of the conventional start-time optimization scheme. This penalty is perpetual and thus a burden especially in networks with few failures. In this work, we suppress that penalty while reducing the worst congestion ratio by considering both failure and non failure scenarios. Our proposed scheme, PSO-NP, is simple and effective in that regard. We expand PSO-NP into a Generalized Preventive Start-time Optimization (GPSO) to find a link weight set that balances both the penalty under no failure and the congestion ratio under the worst case failure. Simulation results show that PSO-NP achieves substantial congestion reduction for any failure case while suppressing the penalty in case of no failure in the network. In addition, GPSO as framework is effective in determining a suitable link weight set that considers the trade off between the penalty under non failure and the worst case congestion ratio reduction.

Link duplication is widely used in Internet protocol networks to tackle the network congestion increase caused by link failure. Network congestion represents the highest link utilization over all the links in the network. Due to capital expenditure constraints, not every link can be duplicated to reduce congestion after a link fails. Giving priority to some selected links makes sense. Meanwhile, traffic routes are determined by link weights that are configured in advance. Therefore, choosing an appropriate set of link weights reduces the number of links that actually need to be duplicated in order to keep a manageable congestion under failure. A manageable congestion is a congestion under which Service Level Agreements can be met. The conventional scheme fixes link weights before determining links to duplicate. In this scheme, the fixed link weights are optimized to minimize the worst network congestion. The worst network congestion is the highest network congestion over all the single non-duplicated link failures. As the selection of links for protection depends on the fixed link weights, some suitable protection patterns, which are not considered with other possible link weights, might be skipped leading to overprotection. The paper proposes a scheme that considers multiple protection scenarios before optimizing link weights in order to reduce the overall number of protected links. Simulation results show that the proposed scheme uses fewer link protections compared to the conventional scheme.

The energy consumption of the Internet has a huge impact on the world economy and it is likely to increase every year. In present backbone networks, pairs of nodes are connected by “bundles” of multiple physical cables that form one logical link and energy saving can be achieved by shutting down unused network resources. The hose model can support traffic demand variations among node pairs in different time periods because it accommodates multiple traffic matrices unlike the pipe model which supports only one traffic matrix. This paper proposes an OSPF (Open Shortest Path First) link weight optimization scheme to reduce the network resources used for the hose model considering single link failures. The proposed scheme employs a heuristic algorithm based on simulated annealing to determine a suitable set of link weights to reduce the worst-case total network resources used, and considering any single link failure preemptively. It efficiently selects the worst-case performance link-failure topology and searches for a link weight set that reduces the worst-case total network resources used. Numerical results show that the proposed scheme is more effective in the reduction of worst-case total network resources used than the conventional schemes, Start-time Optimization and minimum hop routing.