Size-based scheduling to improve web performance
ACM Transactions on Computer Systems (TOCS)
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Proceedings of the 39th Annual IEEE/ACM International Symposium on Microarchitecture
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NSDI'06 Proceedings of the 3rd conference on Networked Systems Design & Implementation - Volume 3
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ACM SIGOPS Operating Systems Review
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Injecting realistic burstiness to a traditional client-server benchmark
ICAC '09 Proceedings of the 6th international conference on Autonomic computing
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Proceedings of the 1st ACM symposium on Cloud computing
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Proceedings of the 7th international conference on Autonomic computing
Economical and Robust Provisioning of N-Tier Cloud Workloads: A Multi-level Control Approach
ICDCS '11 Proceedings of the 2011 31st International Conference on Distributed Computing Systems
Cloud Management: Challenges and Opportunities
IPDPSW '11 Proceedings of the 2011 IEEE International Symposium on Parallel and Distributed Processing Workshops and PhD Forum
The Impact of Soft Resource Allocation on n-Tier Application Scalability
IPDPS '11 Proceedings of the 2011 IEEE International Parallel & Distributed Processing Symposium
Region scheduling: efficiently using the cache architectures via page-level affinity
ASPLOS XVII Proceedings of the seventeenth international conference on Architectural Support for Programming Languages and Operating Systems
Agile middleware for scheduling: meeting competing performance requirements of diverse tasks
Proceedings of the 5th ACM/SPEC international conference on Performance engineering
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Simultaneously achieving good performance and high resource utilization is an important goal for production cloud environments. Through extensive measurements of an n-tier application benchmark (RUBBoS), we show that system response time frequently presents large scale fluctuations (e.g., ranging from tens of milliseconds up to tens of seconds) during periods of high resource utilization. Except the factor of bursty workload from clients, we found that the large scale response time fluctuations can be caused by some system environmental conditions (e.g., L2 cache miss, JVM garbage collection, inefficient scheduling policies) that commonly exist in n-tier applications. The impact of these system environmental conditions can largely amplify the end-to-end response time fluctuations because of the complex resource dependencies in the system. For instance, a 50ms response time increase in the database tier can be amplified to 500ms end-to-end response time increase. We evaluate three heuristics to stabilize response time fluctuations while still achieving high resource utilization in the system. Our results show that large scale response time fluctuations should be taken into account when designing effective autonomous self-scaling n-tier systems in cloud.