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|Title:||Controlled synthesis of traffic matrices|
|Citation:||IEEE ACM Transactions on Networking, 2017; 25(3):1582-1592|
|Paul Tune and Matthew Roughan|
|Abstract:||The traffic matrix (TM) is a chief input in many network design and planning applications. In this paper, we propose a model, called the spherically additive noise model (SANM). In conjunction with iterative proportional fitting (IPF), it enables fast generation of synthetic TMs around a predicted TM. We analyze SANM and IPF’s action on the model to show theoretical guarantees on asymptotic convergence, in particular, convergence to the well-known gravity model.|
|Keywords:||Internet traffic matrix; iterative proportional fitting; sensitivity analysis; synthetic generation|
|Description:||Date of publication January 24, 2017; date of current version June 14, 2017.|
|Rights:||© 2017 IEEE|
|Appears in Collections:||Aurora harvest 8|
Mathematical Sciences publications
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