Optimizing OSPF/IS-IS weights in a changing world

A system of techniques is presented for optimizing open shortest path first (OSPF) or intermediate system-intermediate system (IS-IS) weights for intradomain routing in a changing world, the goal being to avoid overloaded links. We address predicted periodic changes in traffic as well as problems arising from link failures and emerging hot spots     

Efficient techniques and tools for intra‐domain traffic engineering

Intra‐domain routing protocols are based on Shortest Path First (SPF) routing, where shortest paths are calculated between each pair of nodes (routers) using pre‐assigned link weights, also referred to as link metric. These link weights can be modified by network administrators in accordance with the routing policies of the network operator. The operator's objective is usually to minimize traffic congestion or minimize total routing costs subject to the traffic demands and the protocol constraints. However, determining a link weight combination that meets a network operator's objectives is a difficult task. In this paper, we study the link weight optimization problem in intra‐domain networks. This problem is proved to be NP‐hard with hard protocol constraints, e.g., a flow is evenly distributed along the shortest paths between its origin and destination nodes. We present two fast heuristic approaches to generate efficient link metrics for intra‐domain routing. Some promising experimental results are reported.     

Applications of meta‐heuristics to traffic engineering in IP networks

Intra‐domain routing protocols are based on shortest path first (SPF) routing, where shortest paths are calculated between each pair of nodes (routers) using pre‐assigned link weights, also referred to as link metric. These link weights can be modified by network administrators in accordance with the routing policies of the network operator. The operator's objective is usually to minimize traffic congestion or minimize total routing cost subject to the traffic demands and the protocol constraints. However, determining a link weights combination that best suits the network operator's requirements is a difficult task. This paper provides a survey of meta‐heuristic approaches to traffic engineering, focusing on local search approaches and extensions to the basic problem taking into account changing demands and robustness issues with respect to network failures.     

Traffic engineering with traditional IP routing protocols

Traffic engineering involves adapting the routing of traffic to network conditions, with the joint goals of good user performance and efficient use of network resources. We describe an approach to intradomain traffic engineering that works within the existing deployed base of interior gateway protocols, such as Open Shortest Path First and Intermediate System-Intermediate System. We explain how to adapt the configuration of link weights, based on a networkwide view of the traffic and topology within a domain. In addition, we summarize the results of several studies of techniques for optimizing OSPF/IS-IS weights to the prevailing traffic. The article argues that traditional shortest path routing protocols are surprisingly effective for engineering the flow of traffic in large IP networks.     

Fill-rate service level constrained distribution network design

The design of distribution networks that simultaneously consider location and inventory decisions seeks to balance costs and product availability. The most commonly observed measure of product availability in practical settings is the fill-rate service level. However, the optimal design of a distribution network that considers the fill rate to control shortages of fast-moving consumer goods (FMCG) is considered intractable and has only been addressed by heuristic methods. This paper addresses the optimal design of a distribution network for FMCG able to provide high fill-rate service level under a continuous review $(r,Q)$ policy. Considering the exact formulation for the provided fill rate, we formulated a joint location–inventory model with fill-rate service level constraints as a convex mixed integer nonlinear problem for which a novel decomposition-based outer approximation algorithm is proposed. Numerical experiments have shown that our solution approach provides good-quality solutions that are on average 0.15% and, at worst, 2.2% from the optimal solution.