Article ID Journal Published Year Pages File Type
6874498 Journal of Computational Science 2017 32 Pages PDF
Abstract
Traffic matrices, abstract representations of demand, are essential for network operators endeavoring to model, measure, maintain, and improve the efficiency of their complex and heterogeneous architectures. Traffic matrix estimation consists in inferring a traffic matrix from link-level measurements. Provoked by the need to enable agile deployment of new services while, at the same time, slashing operating expenditure and energy consumption, the trend in telecommunications is to shift functionality from physical appliances to virtualized services. We analyze the effects of this landscape change on traffic matrices, their dynamics, and their estimation, indicating some new challenges and problems that will arise in all the associated modeling, analysis and evaluation activities.
Related Topics
Physical Sciences and Engineering Computer Science Computational Theory and Mathematics
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