Title: Automatic Analysis, Decomposition and Parallel Optimization of Large Homogeneous Networks,
Abstract: The life of the modern world essentially depends on the work of the large
artificial homogeneous networks, such as wired and wireless communication
systems, networks of roads and pipelines. The support of their effective
continuous functioning requires automatic screening and permanent optimization
with processing of the huge amount of data by high-performance distributed
systems. We propose new meta-algorithm of large homogeneous network analysis,
its decomposition into alternative sets of loosely connected subnets, and
parallel optimization of the most independent elements. This algorithm is based
on a network-specific correlation function, Simulated Annealing technique, and
is adapted to work in the computer cluster. On the example of large wireless
network, we show that proposed algorithm essentially increases speed of
parallel optimization. The elaborated general approach can be used for analysis
and optimization of the wide range of networks, including such specific types
as artificial neural networks or organized in networks physiological systems of
living organisms.