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Towards Understanding Complex Communication Networks: Performance, Phase Transitions and Control
Published
Author(s)
Vladimir V. Marbukh
Abstract
Micro dynamics of large-scale communication networks is often described by a Markov process with a large number of locally interacting components. Due to astronomically high number of the Markov process states even for moderate-size networks, finding the entire micro distribution by solving the corresponding Kolmogorov equations is computationally infeasible. The paper proposes mean-field approximations for evaluating macro variables representing measurable and practically important network performance criteria without solving the corresponding Kolmogorov equations for TCP/IP networks under random flow arrivals/departures and multiservice mobile wireless cellular networks. Bifurcations of the non-linear mean-field equations are naturally associated with phase transitions and metastability.
Marbukh, V.
(2007),
Towards Understanding Complex Communication Networks: Performance, Phase Transitions and Control, Mathematical Performance Modeling and Analysis | 9th | 2007 | MAMA07, San Diego, CA, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=51184
(Accessed October 12, 2025)