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CCMPerf: A Benchmarking Tool for CORBA Component Model Implementations
Authors:Email author" target="_blank">Arvind?S?KrishnaEmail author  Balachandran?Natarajan  Aniruddha?Gokhale  Douglas?C?Schmidt  Nanbor?Wang  Gautam?Thaker
Affiliation:(1) Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN, USA;(2) Computer Science Department, Washington University, St. Louis, MO, USA;(3) Lockheed Martin Advanced Technology Labs, Cherry Hill, NJ, USA
Abstract:Commercial off-the-shelf (COTS) middleware is now widely used to develop distributed real-time and embedded (DRE) systems. DRE systems are themselves increasingly combined to form ldquosystems of systemsrdquo that have diverse quality of service (QoS) requirements. Earlier generations of COTS middleware, such as Object Request Brokers (ORBs) based on the CORBA 2.x standard, did not facilitate the separation of QoS policies from application functionality, which made it hard to configure and validate complex DRE applications. The new generation of component middleware, such as the CORBA Component Model (CCM) based on the CORBA 3.0 standard, addresses the limitations of earlier generation middleware by establishing standards for implementing, packaging, assembling, and deploying component implementations.There has been little systematic empirical study of the performance characteristics of component middleware implementations in the context of DRE systems. This paper therefore provides four contributions to the study of CCM for DRE systems. First, we describe the challenges involved in benchmarking different CCM implementations. Second, we describe key criteria for comparing different CCM implementations using key black-box and white-box metrics. Third, we describe the design of our CCMPerf benchmarking suite to illustrate test categories that evaluate aspects of CCM implementation to determine their suitability for the DRE domain. Fourth, we use CCMPerf to benchmark CIAO implementation of CCM and analyze the results. These results show that the CIAO implementation based on the more sophisticated CORBA 3.0 standard has comparable DRE performance to that of the TAO implementation based on the earlier CORBA 2.x standard.Arvind S. Krishna is a PhD student in the Electrical Engineering and Computer Science Department at Vanderbilt University and a member of the Institute for Software Integrated Systems. He received his MA in management from the Brila Institute for Technology and Science (BITS), Pilani, India and his MS in computer science from University of California, Irvine. His research interests include patterns, real-time Java technologies for Real-Time Corba, model-integrated QA techniques, and tools for partial evaluation and specialization of middleware. He is a student member of the IEEE and ACM. Contact him at the Inst. for Software Integrated Systems, 2015 Terrace Pl., Nashville, TN 37203.Balachandran Natarajan is a senior staff engineer at the Institute for Software Integrated Systems and a PhD student in electrical engineering and computer science at Vanderbilt University. His research focuses on applying patterns, optimization principles, and frameworks to build high-performance, dependable, and real-time distributed systems. He received his MS in computer science from Washington University. Contact him at the Inst. for Software Integrated Systems, 2015 Terrace Pl., Nashville, TN 37203.Aniruddha Gokhale is an assistant professor in the Electrical Engineering and Computer Science Department at Vanderbilt University and a senior research scientist at the Institute for Software Integrated Systems. His research focuses on real-time component middleware optimizations, distributed systems and networks, model-driven software synthesis applied to component middleware-based distributed systems, and distributed resource management. He received his PhD in computer science from Washington University. Contact him at the Inst. for Software Integrated Systems, 2015 Terrace Pl., Nashville, TN 37203.Douglas C. Schmidt is a professor in the Electrical Engineering and Computer Science Department at Vanderbilt University and a senior research scientist at the Institute for Software Integrated Systems. His research interests include patterns, optimization techniques, and empirical analyses of software frameworks and domain-specific modeling environments that facilitate the development of distributed real-time and embedded middleware and applications running over high-speed networks and embedded system interconnects. He received his PhD in information and computer science at the University of California, Irvine. Contact him at the Inst. for Software Integrated Systems, 2015 Terrace Pl., Nashville, TN 37203.Nanbor Wang is a Research Scientist in the Distributed Technologies Group at the Tech-X Corporation in Boulder, Colorado. He received M.S. and Ph.D. degrees in Computer Science from Washington University in St. Louis, Missouri. While working for his degree, he also worked as a Research Associate in the Center of Distributed Object Computing in the Department of Computer Science where he conducted research on design, implementation and analysis of object-oriented and component-based techniques for development of distributed systems and management of extra-functional concerns. Dr. Wangrsquos work currently focuses on developing and applying middleware techniques, such as CORBA and Grid Computing, for enabling distributed and parallel scientific applications, such as, distributed data analysis, remote visualization and collaboration, and, work-flow management for large-scale scientific applications.Gautam H. Thaker was born in Amdavad, India, in 1955. He holds a BSEE (75) and MSEE (77) from Clemson University, Clemson, SC. He spent the 85-86 academic year at M.I.T. as a visiting researcher. His research interests include analysis, design, construction and validation of real-time, command and control systems. In particular he has focused on interactions between operating systems, networking protocols, and middleware technologies.
Keywords:CCM  benchmarking  CCMPerf  white-box metrics  black-box metrics
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