A parallel textured algorithm for optimal routing in data network

A textured decomposition-based algorithm is developed to solve the optimal routing problem in data networks. The idea of the algorithm is to decompose the large-scale network into several smaller-scale subnetworks; then these subnetworks are organized systematically into several levels. Each level contains mutually independent subnetworks. When the external flows to a level are frozen, one can concurrently compute the optimal solution of the subnetworks at the level. The proposed parallel-oriented algorithm will converge to the global optimal solution when some conditions are satisfied. The authors use a few examples to illustrate the convergence conditions of the textured algorithm. A numerical example to demonstrate the potential speedup of the algorithm is also provided