Quantitative system performance: computer system analysis using queueing network models
Quantitative system performance: computer system analysis using queueing network models
The influence of service-time variability in a closed network of queues
Performance Evaluation
The Markov-modulated Poisson process (MMPP) cookbook
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IEEE/ACM Transactions on Networking (TON)
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Proceedings of the 1996 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
Open, Closed, and Mixed Networks of Queues with Different Classes of Customers
Journal of the ACM (JACM)
Mean-Value Analysis of Closed Multichain Queuing Networks
Journal of the ACM (JACM)
AMVA techniques for high service time variability
Proceedings of the 2000 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
Decomposability, instabilities, and saturation in multiprogramming systems
Communications of the ACM
Introduction to Linear Optimization
Introduction to Linear Optimization
New Linear Program Performance Bounds for Closed QueueingNetworks
Discrete Event Dynamic Systems
Performance Evaluation of Complex Systems: Techniques and Tools, Performance 2002, Tutorial Lectures
Queueing Networks and Markov Chains
Queueing Networks and Markov Chains
Editorial: Long range dependence and heavy tail distributions
Performance Evaluation - Long range dependence and heavy tail distributions
SIGMETRICS '06/Performance '06 Proceedings of the joint international conference on Measurement and modeling of computer systems
Long-Range Dependence at the Disk Drive Level
QEST '06 Proceedings of the 3rd international conference on the Quantitative Evaluation of Systems
Performance impacts of autocorrelated flows in multi-tiered systems
Performance Evaluation
Performance-Guided Load (Un)balancing under Autocorrelated Flows
IEEE Transactions on Parallel and Distributed Systems
A Markovian approach for modeling packet traffic with long-range dependence
IEEE Journal on Selected Areas in Communications
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ACM SIGMETRICS Performance Evaluation Review
KPC-Toolbox: best recipes toward automatization of workload fitting
ACM SIGMETRICS Performance Evaluation Review
Model Identification for Energy-Aware Management of Web Service Systems
ICSOC '08 Proceedings of the 6th International Conference on Service-Oriented Computing
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Higher-order distributional properties in closed queueing networks
Performance Evaluation
International Journal of Information and Computer Security
Automatic stress testing of multi-tier systems by dynamic bottleneck switch generation
Proceedings of the 10th ACM/IFIP/USENIX International Conference on Middleware
BAP: a benchmark-driven algebraic method for the performance engineering of customized services
Proceedings of the first joint WOSP/SIPEW international conference on Performance engineering
Black-box performance models for virtualized web service applications
Proceedings of the first joint WOSP/SIPEW international conference on Performance engineering
Automatic stress testing of multi-tier systems by dynamic bottleneck switch generation
Middleware'09 Proceedings of the ACM/IFIP/USENIX 10th international conference on Middleware
IO performance prediction in consolidated virtualized environments
Proceedings of the 2nd ACM/SPEC International Conference on Performance engineering
Correlated phase-type distributed random numbers as input models for simulations
Performance Evaluation
A class of tractable models for run-time performance evaluation
ICPE '12 Proceedings of the 3rd ACM/SPEC International Conference on Performance Engineering
Performance models of storage contention in cloud environments
Software and Systems Modeling (SoSyM)
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Burstiness and temporal dependence in service processes are often found in multi-tier architectures and storage devices and must be captured accurately in capacity planning models as these features are responsible of significant performance degradations. However, existing models and approximations for networks of first-come first-served (FCFS) queues with general independent (GI) service are unable to predict performance of systems with temporal dependence in workloads. To overcome this difficulty, we define and study a class of closed queueing networks where service times are represented by Markovian Arrival Processes (MAPs), a class of point processes that can model general distributions, but also temporal dependent features such as burstiness in service times. We call these models MAP queueing networks. We introduce provable upper and lower bounds for arbitrary performance indexes (e.g., throughput, response time, utilization) that we call Linear Reduction (LR) bounds. Numerical experiments indicate that LR bounds achieve a mean accuracy error of 2 percent. The result promotes LR bounds as a versatile and reliable bounding methodology of the performance of modern computer systems.