Abstract:
This paper presents a method and tool named the Dataflow Model Auto-Constructor (DMAC). DMAC uses frequent-sequence mining and Dempster-Shafer theory to mine a system exe...Show MoreMetadata
Abstract:
This paper presents a method and tool named the Dataflow Model Auto-Constructor (DMAC). DMAC uses frequent-sequence mining and Dempster-Shafer theory to mine a system execution trace and reconstruct its corresponding dataflow model. Distributed system testers then use the resultant dataflow model to analyze performance properties (e.g., end-to-end response time, throughput, and service time) captured in the system execution trace. Results from applying DMAC to different case studies show that DMAC can reconstruct dataflow models that cover at most 94% of the events in the original system execution trace. Likewise, more than 2 sources of evidence are needed to reconstruct dataflow models for systems with multiple execution contexts.
Published in: 16th IEEE International Symposium on Object/component/service-oriented Real-time distributed Computing (ISORC 2013)
Date of Conference: 19-21 June 2013
Date Added to IEEE Xplore: 02 October 2014
Electronic ISBN:978-1-4799-2111-9