Capacity planning for Web performance: metrics, models, and methods
Capacity planning for Web performance: metrics, models, and methods
Mean-Value Analysis of Closed Multichain Queuing Networks
Journal of the ACM (JACM)
Web traffic modeling and Web server performance analysis
ACM SIGMETRICS Performance Evaluation Review
Traffic model and performance evaluation of Web servers
Performance Evaluation
An analytical model for multi-tier internet services and its applications
SIGMETRICS '05 Proceedings of the 2005 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
Performance impacts of autocorrelated flows in multi-tiered systems
Performance Evaluation
Bound analysis of closed queueing networks with workload burstiness
SIGMETRICS '08 Proceedings of the 2008 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
KPC-Toolbox: Simple Yet Effective Trace Fitting Using Markovian Arrival Processes
QEST '08 Proceedings of the 2008 Fifth International Conference on Quantitative Evaluation of Systems
A Markovian approach for modeling packet traffic with long-range dependence
IEEE Journal on Selected Areas in Communications
Burstiness in multi-tier applications: symptoms, causes, and new models
Proceedings of the 9th ACM/IFIP/USENIX International Conference on Middleware
JMT: performance engineering tools for system modeling
ACM SIGMETRICS Performance Evaluation Review
User-friendly approach to capacity planning studies with Java modelling tools
Proceedings of the 2nd International Conference on Simulation Tools and Techniques
A Realistic Integrated Model of Parallel System Workloads
CCGRID '10 Proceedings of the 2010 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing
A trace-based service level planning framework for enterprise application clouds
Proceedings of the 7th International Conference on Network and Services Management
Defragmenting the cloud using demand-based resource allocation
Proceedings of the ACM SIGMETRICS/international conference on Measurement and modeling of computer systems
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Although recent advances in theory indicate that burstiness in the service time process can be handled effectively by queueing models (e.g.,MAP queueing networks [2]), there is a lack of understanding and of practical results on how to perform model parameterization, especially when this parameterization must be derived from limited coarse measurements. We propose a new parameterization methodology based on the index of dispersion of the service process at a server, which is inferred by observing the number of completions within the concatenated busy periods of that server. The index of dispersion together with other measurements that reflect the "estimated" mean and the 95th percentile of service times are used to derive a MAP process that captures well burstiness of the true service process. Detailed experimentation on a TPC-W testbed where all measurements are obtained via a commercially available tool, the HP (Mercury) Diagnostics, shows that the proposed technique offers a simple yet powerful solution to the difficult problem of inferring accurate descriptors of the service time process from coarse measurements. Experimental and model prediction results are in excellent agreement and argue strongly for the effectiveness of the proposed methodology under bursty or simply variable workloads.