SelfTalk for Dena: query language and runtime support for evaluating system behavior
ACM SIGOPS Operating Systems Review
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Proceedings of the ACM SIGMETRICS international conference on Measurement and modeling of computer systems
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Proceedings of the 2011 ACM Symposium on Applied Computing
Modellus: Automated modeling of complex internet data center applications
ACM Transactions on the Web (TWEB)
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Proceedings of the 28th Annual ACM Symposium on Applied Computing
Performance troubleshooting in data centers: an annotated bibliography?
ACM SIGOPS Operating Systems Review
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Large amount of monitoring data can be collected from distributed systems as the observables to analyze system behaviors. However, without reasonable models to characterize systems, we can hardly interpret such monitoring data effectively for system management. In this paper, a new concept named flow intensity is introduced to measure the intensity with which internal monitoring data reacts to the volume of user requests in distributed transaction systems. We propose a novel approach to automatically model and search relationships between the flow intensities measured at various points across the system. If the modeled relationships hold all the time, they are regarded as invariants of the underlying system. Experimental results from a real system demonstrate that such invariants widely exist in distributed transaction systems. Further we discuss how such invariants can be used to characterize complex systems and support autonomic system management.