Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/12092
Title: Towards a physics of Internet traffic in a geographic network
Contributor(s): Baker, Robert G  (author)
Publication Date: 2012
DOI: 10.1016/j.physa.2011.10.002
Handle Link: https://hdl.handle.net/1959.11/12092
Abstract: A set of equations from a biased random walk are shown to describe the time-based Gaussian distributions of Internet traffic relative to the Earth's time zones. The Internet is an example of a more general physical problem dealing with motion near the speed of light relative to different time frames of reference. The second order differential equation (DE) takes the form of 'time diffusion' near the speed of light or alternatively considered as a complex variable with real time and imaginary longitudinal components. Congestion waves are generated by peak global traffic from different time zones following the Earth's revolution. The DE is divided into space and time operators for discussion and each component solution, including constants, is illustrated using data from a global network compiled by the Stanford Linear Accelerator Centre (SLAC). Indices of global and regional phase congestion for the monitoring sites are calculated from standardised regressions from the Earth's rotation. There is also a J-curve limit to transferring information by the Internet and this is expressed as an inequality underpinned by the speed of light with examples from US and European traffic. The research returns to an often little known theme of Isaac Newton's: mixing physics with geography. In our case, the equations define trajectories of information packets travelling near the speed of light, navigating within networks and between longitudes, relative to the Earth's rotation.
Publication Type: Journal Article
Source of Publication: Physica A: Statistical Mechanics and its Applications, 391(4), p. 1133-1148
Publisher: Elsevier BV
Place of Publication: North Holland
ISSN: 1873-2119
0378-4371
Field of Research (FOR): 010401 Applied Statistics
Socio-Economic Objective (SEO): 970101 Expanding Knowledge in the Mathematical Sciences
Peer Reviewed: Yes
HERDC Category Description: C1 Refereed Article in a Scholarly Journal
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