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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, North-Holland | Place of Publication: | Netherlands | ISSN: | 1873-2119 0378-4371 |
Fields of Research (FoR) 2008: | 010401 Applied Statistics | Fields of Research (FoR) 2020: | 490501 Applied statistics | Socio-Economic Objective (SEO) 2008: | 970101 Expanding Knowledge in the Mathematical Sciences | Socio-Economic Objective (SEO) 2020: | 280118 Expanding knowledge in the mathematical sciences | Peer Reviewed: | Yes | HERDC Category Description: | C1 Refereed Article in a Scholarly Journal |
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Appears in Collections: | Journal Article |
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