MMLU in Network Flow Optimization
In a previous post, I discussed how Maximum Flow problems can be used for network optimization. We focused on a scenario where demands were already routed in the network, and our objective was to determine the maximum demand that could be handled between a given source and a destination metro. We solved this problem by calculating the residual bandwidth for the graph, creating fake demand nodes for each metro with high-capacity edges to avoid them being bottlenecks, and applying Dinic’s algorithm between the source and the destination metro. This is also called a Single Commodity Flow Problem.
We then extended the problem to consider two metros sending traffic to the same destination sink and used the Network Simplex algorithm to determine the maximum traffic the network could accommodate. This is also known as a Multi Commodity Flow Problem. Finally, we validated our findings by routing the results through a network model.
In this post, we will discuss another constraint-based problem called Minimum Maximum Link Utilization (MMLU). The primary goal of MMLU is to route traffic demands in a network to minimize the maximum link utilization. In other words, we aim to distribute the traffic evenly across the network links to Continue reading
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