Paper Info
Title
Congestion probabilities in a batched Poisson multirate loss model supporting elastic and adaptive traffic.
Abstract
The ever increasing demand of elastic and adaptive services, where in-service calls can tolerate bandwidth compression/expansion, together with the bursty nature of traffic, necessitates a proper teletraffic loss model which can contribute to the call-level performance evaluation of modern communication networks. In this paper, we propose a multirate loss model that supports elastic and adaptive traffic, under the assumption that calls arrive in a single link according to a batched Poisson process (a more “bursty” process than the Poisson process, where calls arrive in batches). We assume a general batch size distribution and the partial batch blocking discipline, whereby one or more calls of a new batch are blocked and lost, depending on the available bandwidth of the link. The proposed model does not have a product form solution, and therefore we propose approximate but recursive formulas for the efficient calculation of time and call congestion probabilities, link utilization, average number of calls in the system, and average bandwidth allocated to calls. The consistency and the accuracy of the model are verified through simulation and found to be quite satisfactory.
Year
DOI
Venue
2013
10.1007/s12243-012-0326-7
Annales des Télécommunications
Keywords
Field
DocType
Batched Poisson process, Elastic–adaptive traffic, Recursive formula, Time–call congestion, Markov chain
Product-form solution,Mathematical optimization,Telecommunications network,Computer science,Bandwidth compression,Markov chain,Computer network,Electronic engineering,Bandwidth (signal processing),Poisson distribution,Elasticity (economics),Recursion
Journal
Volume
Issue
ISSN
68
5-6
1958-9395
Citations 
PageRank 
References 
22
0.80
31
Authors
4
Name
Order
Citations
PageRank
Ioannis D. Moscholios131833.14
J. S. Vardakas29817.23
Michael D. Logothetis3765.01
Anthony C. Boucouvalas423821.91