Scaling Theory for Information Networks

AuthorsMelanie Moses
Stephanie Forrest
Al Davis
Michael Lodder
James Brown


Networks distribute energy, materials and information to the components of a variety of natural and human-engineered systems, including organisms, brains, the Internet, and computer chips. Distribution networks enable integrated and coordinated functioning of these systems, and they also constrain their design. Metabolic Scaling Theory (MST) shows that the rate at which networks deliver energy to an organism is proportional to its mass raised to the 3/4 power. We show that computational systems are also characterized by nonlinear network scaling. We use MST principles to characterize information networks, and as a specific example we show how network scaling predicts properties of clock distribution networks in microprocessors. Based on the scaling of the clock distribution network, we predict a set of tradeoffs and performance properties that scale with chip size and number of transistors. We highlight similarities and differences between networks on computer chips and biological networks. More generally, we hypothesize a set of constraints between the size, power and performance of networked information systems including transistors on chips, hosts on the Internet, and neurons in the brain.

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