QD-AMVA: evaluación de sistemas con requisitos de servicio dependientes de la cola
| Autor: | Juan F. Prez, Giuliano Casale, Weikun Wang |
|---|---|
| Rok vydání: | 2015 |
| Předmět: |
Mathematical optimization
Queueing theory Computer science business.industry Product-form Computer Networks and Communications Computation Distributed computing Approximate mean value analysis Workload Cloud computing State-dependent service Enterprise system Robustness (computer science) Hardware and Architecture Modeling and Simulation Modelling and Simulation Closed queueing network business Software |
| Zdroj: | Performance Evaluation Repositorio EdocUR-U. Rosario Universidad del Rosario instacron:Universidad del Rosario |
| ISSN: | 0166-5316 |
| DOI: | 10.1016/j.peva.2015.06.006 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|
Full Text from ScienceDirect