On the self-similar nature of Ethernet traffic (extended version)
IEEE/ACM Transactions on Networking (TON)
The benchmark book
Long-lasting transient conditions in simulations with heavy-tailed workloads
Proceedings of the 29th conference on Winter simulation
Generating representative Web workloads for network and server performance evaluation
SIGMETRICS '98/PERFORMANCE '98 Proceedings of the 1998 ACM SIGMETRICS joint international conference on Measurement and modeling of computer systems
A Framework for Computer Performance Evaluation Using Benchmark Sets
IEEE Transactions on Computers
MASCOTS '99 Proceedings of the 7th International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems
Queueing Networks and Markov Chains
Queueing Networks and Markov Chains
Long-Range Dependence at the Disk Drive Level
QEST '06 Proceedings of the 3rd international conference on the Quantitative Evaluation of Systems
A Synthetic Workload Generation Technique for Stress Testing Session-Based Systems
IEEE Transactions on Software Engineering
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
Burstiness in multi-tier applications: symptoms, causes, and new models
Proceedings of the 9th ACM/IFIP/USENIX International Conference on Middleware
Injecting realistic burstiness to a traditional client-server benchmark
ICAC '09 Proceedings of the 6th international conference on Autonomic computing
Automatically generating bursty benchmarks for multitier systems
ACM SIGMETRICS Performance Evaluation Review
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The performance of multi-tier systems is known to be significantly degraded by workloads that place bursty service demands on system resources. Burstiness can cause queueing delays, oversubscribe limited threading resources, and even cause dynamic bottleneck switches between resources. Thus, there is need for a methodology to create benchmarks with controlled burstiness and bottleneck switches to evaluate their impact on system performance. We tackle this problem using a model-based technique for the automatic and controlled generation of bursty benchmarks. Markov models are constructed in an automated manner to model the distribution of service demands placed by sessions of a given system on various system resources. The models are then used to derive session submission policies that result in user-specified levels of service demand burstiness for resources at the different tiers in a system. Our approach can also predict under what conditions these policies can create dynamic bottleneck switching among resources. A case study using a three-tier TPC-W testbed shows that our method is able to control and predict burstiness for session service demands. Further, results from the study demonstrate that our approach was able to inject controlled bottleneck switches. Experiments show that these bottleneck switches cause dramatic latency and throughput degradations that are not shown by the same session mix with non-bursty conditions.