  We present a general holistic theory for the organization of complex
networks, both human-engineered and naturally-evolved. Introducing concepts of
value of interactions and satisfaction as generic network performance measures,
we show that the underlying organizing principle is to meet an overall
performance target for wide-ranging operating or environmental conditions. This
design or survival requirement of reliable performance under uncertainty leads,
via the maximum entropy principle, to the emergence of a power law vertex
degree distribution. The theory also predicts exponential or Poisson degree
distributions depending on network redundancy, thus explaining all three
regimes as different manifestations of a common underlying phenomenon within a
unified theoretical framework.
