Importance

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Abstract

A system and method for optimizing placement of network equipment and information load in a network over a period of time. A demand input structure having a plurality of demands organized by their time points and MUX levels is provided as an input to a model generator and an optimization processor associated therewith. Starting with the earliest demand with the highest MUX level to be serviced by the network, a directed graph network model is obtained by using appropriate transformation techniques. A MUX modularity constraint is imposed in order to obtain a filtered network model that can support a MUX level of a selected demand at a particular time point. A cost function associated with the filtered network model is constructed using a flow cost term and an equipment cost term. Appropriate constraints are imposed on the cost function for optimization. A solution set comprising network placement information and demand routing information is obtained for a MUX level at a current time point. When the next MUX level of the demand is taken up for optimization, the filtered network model and associated cost function are recursively updated by using the solution set obtained for the previous MUX level. The recursive optimization process takes place for each time point, covering all MUX levels at that time point, as provided in the demand input structure. Preferably, Priority 1 demands are optimized first. Thereafter, Priority 2 demands are optimized by employing a capacitated shortest path algorithm with respect to each Priority 2 demand presented in its order.

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First Claim