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Abstract

A methodology for optimizing the placement of network “Points of Presence” (POPs) across the carrier's entire network (i.e., a “global” solution”) utilizes carefully constructed customer clustering and simulated annealing methodology to create a cost-efficient solution. The customer base is first partitioned into a plurality of clusters such that the customers within each cluster are closer to its centroid than the centroid of any other cluster (e.g., applying the k-means clustering algorithm or any other suitable method of partitioning the customer base). A linear algorithm process is used to minimize the costs associated with the number of placement of POPs within each cluster. A simulated annealing (SA) process is then used to iterate the entire set of potential POP locations until a compact, steady-state solution is achieved (or, alternatively, until a given number of iterations has been performed). In a preferred embodiment, a number of iterations are performed at each “temperature” in the simulating annealing process to further improve the result (this iterative process referred to in the art as “intensification”).

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First Claim