Abstract

The principle of load balancing is to distribute the data load more evenly over the network in order to increase the network performance and efficiency. With dynamic load balancing the routing is undated at certain intervals. This thesis was developed to evaluate load balancing methods in the IP-network of TeliaSonera.Load balancing using short path routing, bottleneck load balancing and load balancing using MPLS have been evaluated. Short path routing is a flow sharing technique that allows routing on paths other than the shortest one. Load balancing using short path routing is achieved by dynamic updates of the link weights. Bottleneck is in its nature a dynamic load balancing algorithm. Unlike load balancing using short path routing it updates the flow sharing, not the metrics. The algorithm uses information about current flow sharing and link loads to detect bottlenecks within the network. The information is used to calculate new flow sharing parameters. When using MPLS, one or more complete routing paths (LSPs) are defined at each edge LSR before sending any traffic. MPLS brings the ability to perform flow sharing by defining the paths to be used and how the outgoing data load is to be shared among these. The model has been built from data about the network supplied by TeliaSonera. The model consists of a topology part, a traffic part, a routing part and cost part. The traffic model consists of a OD demand matrix. The OD demand matrix has been estimated from collected link loads. This was done with estimation models; the gravity model and an optimisation model. The algorithms have been analysed at several scenarios; normal network, core node failure, core link failure and DWDM system failure. A cost function, where the cost increases as the link load increases has been used to evaluate the algorithms. The signalling requirements for implementation of the load balancing algorithm have also been investigated.

Abstract

We conduct a Global Sensitivity Analysis (GSA) of urban-scale network performances to parameters representing a wide range of realistic dynamic loadings, decomposed in a choice of OD matrix, routing alternatives, and paths flow distribution. A special attention is given to the route alternatives generation, where overlapping metrics and selection methods are introduced to reproduce a wide variety of paths sets configuration. Paths flow distributions are calculated based on different equilibrium criteria. Several sets of simulations are conducted and analyzed graphically and then with a variance-based GSA method so as to get insights on how much and in which conditions each network loading parameter influences network performances by itself or by interaction. Results notably reveal that the demand level is the most decisive parameter since low values simply lead to free-flow conditions with no influence of the other parameters, whereas higher values lead to a wide diversity of network states going from close to capacity but stable to gridlocked. While a nonnegligible amount of this disparity is explained by the demand pattern parameter, the number of paths per OD, their overlapping, and the equilibrium criterion of the paths flow distribution are still influential enough to maintain the network close to its optimal capacity or to prevent the network from fast collapse (gridlock). The highlighted connection between spatial and temporal heterogeneities of the network states explains the gridlocking phenomena. These extracted insights are very encouraging for operational implementations. Document type: Article