Performance analysis of traffic surges in multi-class communication networks
In multi-class communication networks, traffic surges due to one class of users can significantly degrade the performance for other classes. During these transient periods, it is thus of crucial importance to implement priority mechanisms allowing the conservation of the quality of service experienc...
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2010
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| Acceso en línea: | https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_97814244_v_n_p_Jonckheere http://hdl.handle.net/20.500.12110/paper_97814244_v_n_p_Jonckheere |
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paper:paper_97814244_v_n_p_Jonckheere2023-06-08T16:37:25Z Performance analysis of traffic surges in multi-class communication networks Asymptotic behaviors Bandwidth allocations Communication networks Complex interaction Multi-class Performance analysis Performance measure Simple networks Stochastic nature Time-scales Time-space Differential equations Quality of service Traffic congestion In multi-class communication networks, traffic surges due to one class of users can significantly degrade the performance for other classes. During these transient periods, it is thus of crucial importance to implement priority mechanisms allowing the conservation of the quality of service experienced by the affected classes, while ensuring that the temporarily unstable class is not entirely neglected. In this paper, we examine - for a suitably-scaled set of parameters - the complex interaction occurring between several classes of traffic when an unstable class is penalized proportionally to its level of congestion. We characterize the evolution of the performance measures of the network from the moment the initial surge takes place until the system reaches its equilibrium. We show that, using a time-space-transition-scaling, the trajectories of the temporarily unstable class can be described by a differential equation, while those of the stable classes retain their stochastic nature. In particular, we show that the temporarily unstable class evolves at a time-scale which is much slower than that of the stable classes. Although the time-scales decouple, the dynamics of the temporarily unstable and the stable classes continue to influence one another. We further proceed to characterize the obtained differential equations for several simple network examples. In particular, the macroscopic asymptotic behavior of the unstable class allows us to gain important qualitative insights on how the bandwidth allocation affects performance. 2010 https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_97814244_v_n_p_Jonckheere http://hdl.handle.net/20.500.12110/paper_97814244_v_n_p_Jonckheere |
| institution |
Universidad de Buenos Aires |
| institution_str |
I-28 |
| repository_str |
R-134 |
| collection |
Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) |
| topic |
Asymptotic behaviors Bandwidth allocations Communication networks Complex interaction Multi-class Performance analysis Performance measure Simple networks Stochastic nature Time-scales Time-space Differential equations Quality of service Traffic congestion |
| spellingShingle |
Asymptotic behaviors Bandwidth allocations Communication networks Complex interaction Multi-class Performance analysis Performance measure Simple networks Stochastic nature Time-scales Time-space Differential equations Quality of service Traffic congestion Performance analysis of traffic surges in multi-class communication networks |
| topic_facet |
Asymptotic behaviors Bandwidth allocations Communication networks Complex interaction Multi-class Performance analysis Performance measure Simple networks Stochastic nature Time-scales Time-space Differential equations Quality of service Traffic congestion |
| description |
In multi-class communication networks, traffic surges due to one class of users can significantly degrade the performance for other classes. During these transient periods, it is thus of crucial importance to implement priority mechanisms allowing the conservation of the quality of service experienced by the affected classes, while ensuring that the temporarily unstable class is not entirely neglected. In this paper, we examine - for a suitably-scaled set of parameters - the complex interaction occurring between several classes of traffic when an unstable class is penalized proportionally to its level of congestion. We characterize the evolution of the performance measures of the network from the moment the initial surge takes place until the system reaches its equilibrium. We show that, using a time-space-transition-scaling, the trajectories of the temporarily unstable class can be described by a differential equation, while those of the stable classes retain their stochastic nature. In particular, we show that the temporarily unstable class evolves at a time-scale which is much slower than that of the stable classes. Although the time-scales decouple, the dynamics of the temporarily unstable and the stable classes continue to influence one another. We further proceed to characterize the obtained differential equations for several simple network examples. In particular, the macroscopic asymptotic behavior of the unstable class allows us to gain important qualitative insights on how the bandwidth allocation affects performance. |
| title |
Performance analysis of traffic surges in multi-class communication networks |
| title_short |
Performance analysis of traffic surges in multi-class communication networks |
| title_full |
Performance analysis of traffic surges in multi-class communication networks |
| title_fullStr |
Performance analysis of traffic surges in multi-class communication networks |
| title_full_unstemmed |
Performance analysis of traffic surges in multi-class communication networks |
| title_sort |
performance analysis of traffic surges in multi-class communication networks |
| publishDate |
2010 |
| url |
https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_97814244_v_n_p_Jonckheere http://hdl.handle.net/20.500.12110/paper_97814244_v_n_p_Jonckheere |
| _version_ |
1768543584198328320 |