QD-AMVA: evaluating systems with queue-dependent service requirements
Workload measurements in enterprise systems often lead to observe a dependence between the number of requests running at a resource and their mean service requirements. However, multiclass performance models that feature these dependences are challenging to analyze, a fact that discourages practitio...
| Autores: | , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2015 |
| País: | Colombia |
| Institución: | Universidad del Rosario |
| Repositorio: | Repositorio EdocUR - U. Rosario |
| Idioma: | inglés |
| OAI Identifier: | oai:repository.urosario.edu.co:10336/26825 |
| Acceso en línea: | https://doi.org/10.1016/j.peva.2015.06.006 https://repository.urosario.edu.co/handle/10336/26825 |
| Access Level: | acceso abierto |
| Palabra clave: | Closed queueing network Product-form Approximate mean value analysis State-dependent service |
| Sumario: | Workload measurements in enterprise systems often lead to observe a dependence between the number of requests running at a resource and their mean service requirements. However, multiclass performance models that feature these dependences are challenging to analyze, a fact that discourages practitioners from characterizing workload dependences. We here focus on closed multiclass queueing networks and introduce QD-AMVA, the first approximate mean-value analysis (AMVA) algorithm that can efficiently and robustly analyze queue-dependent service times in a multiclass setting. A key feature of QD-AMVA is that it operates on mean values, avoiding the computation of state probabilities. This property is an innovative result for state-dependent models, which increases the computational efficiency and numerical robustness of their evaluation. Extensive validation on random examples, a cloud load-balancing case study and comparison with a fluid method and an existing AMVA approximation prove that QD-AMVA is efficient, robust and easy to apply, thus enhancing the tractability of queue-dependent models. |
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