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Author Kuroda, Takayuki ♦ Tambe, Sumant ♦ An, Kyoungho ♦ Gokhale, Aniroddha ♦ Sorbini, Andrea
Source ACM Digital Library
Content type Text
Publisher Association for Computing Machinery (ACM)
File Format PDF
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Computer programming, programs & data
Subject Keyword Model-driven engineering ♦ Generative programming ♦ Publish/subscribe ♦ Performance testing
Abstract The Object Management Group's (OMG) Data Distribution Service (DDS) provides many configurable policies which determine end-to-end quality of service (QoS) of applications. It is challenging to predict the system's performance in terms of latencies, throughput, and resource usage because diverse combinations of QoS configurations influence QoS of applications in different ways. To overcome this problem, design-time formal methods have been applied with mixed success, but lack of sufficient accuracy in prediction, tool support, and understanding of formalism has prevented wider adoption of the formal techniques. A promising approach to address this challenge is to emulate system behavior and gather data on the QoS parameters of interest by experimentation. To realize this approach, which is preferred over formal methods due to their limitations in accurately predicting QoS, we have developed a model-based automatic performance testing framework with generative capabilities to reduce manual efforts in generating a large number of relevant QoS configurations that can be deployed and tested on a cloud platform. This paper describes our initial efforts in developing and using this technology.
Description Affiliation: Vanderbilt University, Nashville, TN, USA (An, Kyoungho; Kuroda, Takayuki; Gokhale, Aniroddha) || RTI, Sunnyvale, CA, USA (Tambe, Sumant; Sorbini, Andrea)
Age Range 18 to 22 years ♦ above 22 year
Educational Use Research
Education Level UG and PG
Learning Resource Type Article
Publisher Date 1983-05-01
Publisher Place New York
Journal ACM SIGPLAN Notices (SIGP)
Volume Number 49
Issue Number 3
Page Count 4
Starting Page 179
Ending Page 182

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Source: ACM Digital Library