ICPE 2019
Date: Apr 06, 2019 6:00 pm – Apr 11, 2019 5:00 am
Location: Mumbai, India
10th ACM/SPEC International Conference on Performance Engineering (ICPE 2019)
The International Conference on Performance Engineering (ICPE) is the leading international forum for presenting and discussing novel ideas, innovations, trends and experiences in the field of performance engineering.
Modern systems, such as big data and machine learning systems, data centers and cloud infrastructures, social networks, peer-to-peer, mobile and wireless systems, cyber-physical systems, the Internet of Things or more traditional systems such as web-based or real-time systems, rely increasingly on distributed and dynamic architectures and pose a challenge the end-to-end performance management. ICPE brings together researchers and practitioners to report state-of-the-art and in-progress research on performance engineering of software and systems, including performance measurement, modeling, benchmark design, and run-time performance management. The focus is both on classical metrics such as response time, throughput, resource utilization, and (energy) efficiency, as well as on the relationship of such metrics to other system properties including but not limited to scalability, elasticity, availability, reliability, cost, sustainability, security and privacy.
Keynote Speakers
Kishor Trivedi holds the Fitzgerald Hudson Chair in the Department of Electrical and Computer Engineering at Duke University, Durham, NC. He has a 1968 B.Tech. (EE) from IIT Mumbai and MS’72/PhD’74 (CS) from the University of Illinois at Urbana-Champaign. He has been on the Duke faculty since 1975. He is the author of a well-known text entitled, Probability and Statistics with Reliability, Queuing and Computer Science Applications, originally published in 1982 by Prentice-Hall which was published as an inexpensive Indian edition by PHI. A thoroughly revised second edition of this book has been published by John Wiley that is also available as an inexpensive Asian edition. The book is recently translated into Chinese. He has also published two other books entitled, Performance and Reliability Analysis of Computer Systems, published by Kluwer Academic Publishers and Queueing Networks and Markov Chains, John Wiley. His fourth book, Reliability and Availability Engineering, is published by Cambridge University Press in 2017. He is a Life Fellow of the Institute of Electrical and Electronics Engineers and a Golden Core Member of IEEE Computer Society. He has published over 600 articles and has supervised 48 Ph.D. dissertations. His h-index is 98. He is the recipient of IEEE Computer Society’s Technical Achievement Award for his research on Software Aging and Rejuvenation. His research interests are in reliability, availability, performance and survivability of computer and communication systems and in software dependability.
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Evgenia Smirni received the Diploma degree in Computer Science and Informatics from the University of Patras, Greece, in 1987 and the Ph.D. degree in Computer Science from Vanderbilt University in 1995. She is the Sidney P. Chockley Professor of Computer Science at the College of William and Mary, Williamsburg, VA, USA. Her research interests include queuing networks, stochastic modeling, Markov chains, resource allocation policies, storage systems, data centers and cloud computing, workload characterization, models for performance prediction, and reliability of distributed systems and applications. She has served as the Program co-Chair of QEST’05, ACM Sigmetrics/Performance’06, HotMetrics’10, ICPE’17, DSN’17, SRDS’19, and HPDC'19. She also served as the General co-Chair of QEST’10 and NSMC’10. She is an ACM Distinguished Scientist.
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Dr N. Muralidaran has over 30+ years of experience as an Information Technology professional in the Financial Services sector. He has a rich experience in building organizations. He has always been result oriented and a great team builder. His positive outlook has helped him in visualizing success in every opportunity that has come his way. In his last assignment as the Chief of Special Projects – NSEIL, he was responsible for the International Business Development and Exchange collaborations, strategic and futuristic technology and new initiatives of the exchange. Prior to this, as CEO of NSE Infotech Services Ltd., the captive IT services unit of NSE, he was responsible for the IT strategy, planning, software development and IT services of the exchange. Before joining the NSE group in 2004, he was the CEO / CTO with the IL&FS group since 1990. In this role he was responsible for strategy planning, design and implementation of IT solutions across different group companies. During this tenure, he was part of the initial core team involved in setting up the National Stock Exchange from conceptualization stage till the initial implementation. He continued to be a part of the exchange in an advisory capacity in different committees. He has also worked with Bhabha Atomic Research Centre (BARC) in the Reactor Analysis and Simulation Systems group and NELCO Ltd in the past.Dr N. Muralidaran holds a Ph.D. from Birla Institute of Technology, Mesra for his work in "Architecture Model for Scaling Mission Critical Real Time Applications for High Performance" - under the management stream. He also holds a PG Diploma in Computer Management and MBA in Finance.
This year's main theme is "performance engineering in the Artificial Intelligence era." We are looking for contributions that use AI techniques to enhance the performance modeling, estimation, and optimization of complex systems. At the same time we are looking for contributions that analyze and improve AI systems.
Topics of interest include, but are not limited to:
Performance modeling of software
* Languages and ontologies
* Methods and tools
* Relationship/integration/tradeoffs with other QoS attributes
* Analytical, simulation and statistical modeling methodologies
* Machine learning and neural networks
* Model validation and calibration techniques
* Automatic model extraction
* Performance modeling and analysis tools
Performance and software development processes/paradigms
* Software performance patterns and anti-patterns
* Software/performance tool interoperability (models and data interchange formats)
* Performance-oriented design, implementation and configuration
management
* Software Performance Engineering and Model-Driven Development
* Gathering, interpreting and exploiting software performance
annotations and data
* System sizing and capacity planning techniques
* (Model-driven) Performance requirements engineering
* Relationship between performance and architecture
* Collaboration of development and operation (DevOps) for performance
* Performance and agile methods
* Performance in Service-Oriented Architectures (SOA)
* Performance of microservice architectures and containers
* DevOps and Performance
Performance measurement, monitoring and analysis
* Performance measurement and monitoring techniques
* Analysis of measured application performance data
* Application tracing and profiling
* Workload characterization techniques
* Experimental design
* Tools for performance testing, measurement, profiling and tuning
Benchmarking
* Performance metrics and benchmark suites
* Benchmarking methodologies
* Development of parameterizable, flexible benchmarks
* Benchmark workloads and scenarios
* Use of benchmarks in industry and academia
Run-time performance management and adaptation
* Machine learning and runtime performance decisions
* Context modeling and analysis
* Runtime model estimation
* Use of models at run-time
* Online performance prediction
* Autonomic resource management
* Utility-based optimization
* Capacity management
Power and performance, energy efficiency
* Power consumption models and management techniques
* Tradeoffs between performance and energy efficiency
* Performance-driven resource and power management
Performance modeling and evaluation in different environments and application domains
* Web-based systems, e-business, Web services
* Big data systems and data analytics
* Deep-learning systems systems
* Internet of Things
* Social networks
* Cyber-physical systems
* Industrial Internet (Industry 4.0)
* Blockchain
* Virtualization and cloud computing
* Autonomous/adaptive systems
* Transaction-oriented systems
* Communication networks
* Parallel and distributed systems
* Embedded systems
* Multi-core systems
* Cluster and grid computing environments
* High performance computing
* Event-based systems
* Real-time and multimedia systems
* Low-latency systems
* Peer-to-peer, mobile and wireless systems
All other topics related to performance of software and systems.
Submitted by Anonymous
on
10th ACM/SPEC International Conference on Performance Engineering (ICPE 2019)
The International Conference on Performance Engineering (ICPE) is the leading international forum for presenting and discussing novel ideas, innovations, trends and experiences in the field of performance engineering.
Modern systems, such as big data and machine learning systems, data centers and cloud infrastructures, social networks, peer-to-peer, mobile and wireless systems, cyber-physical systems, the Internet of Things or more traditional systems such as web-based or real-time systems, rely increasingly on distributed and dynamic architectures and pose a challenge the end-to-end performance management. ICPE brings together researchers and practitioners to report state-of-the-art and in-progress research on performance engineering of software and systems, including performance measurement, modeling, benchmark design, and run-time performance management. The focus is both on classical metrics such as response time, throughput, resource utilization, and (energy) efficiency, as well as on the relationship of such metrics to other system properties including but not limited to scalability, elasticity, availability, reliability, cost, sustainability, security and privacy.
Keynote Speakers
Kishor Trivedi holds the Fitzgerald Hudson Chair in the Department of Electrical and Computer Engineering at Duke University, Durham, NC. He has a 1968 B.Tech. (EE) from IIT Mumbai and MS’72/PhD’74 (CS) from the University of Illinois at Urbana-Champaign. He has been on the Duke faculty since 1975. He is the author of a well-known text entitled, Probability and Statistics with Reliability, Queuing and Computer Science Applications, originally published in 1982 by Prentice-Hall which was published as an inexpensive Indian edition by PHI. A thoroughly revised second edition of this book has been published by John Wiley that is also available as an inexpensive Asian edition. The book is recently translated into Chinese. He has also published two other books entitled, Performance and Reliability Analysis of Computer Systems, published by Kluwer Academic Publishers and Queueing Networks and Markov Chains, John Wiley. His fourth book, Reliability and Availability Engineering, is published by Cambridge University Press in 2017. He is a Life Fellow of the Institute of Electrical and Electronics Engineers and a Golden Core Member of IEEE Computer Society. He has published over 600 articles and has supervised 48 Ph.D. dissertations. His h-index is 98. He is the recipient of IEEE Computer Society’s Technical Achievement Award for his research on Software Aging and Rejuvenation. His research interests are in reliability, availability, performance and survivability of computer and communication systems and in software dependability.
---------------------------------------------------------------------------------------------------------------
Evgenia Smirni received the Diploma degree in Computer Science and Informatics from the University of Patras, Greece, in 1987 and the Ph.D. degree in Computer Science from Vanderbilt University in 1995. She is the Sidney P. Chockley Professor of Computer Science at the College of William and Mary, Williamsburg, VA, USA. Her research interests include queuing networks, stochastic modeling, Markov chains, resource allocation policies, storage systems, data centers and cloud computing, workload characterization, models for performance prediction, and reliability of distributed systems and applications. She has served as the Program co-Chair of QEST’05, ACM Sigmetrics/Performance’06, HotMetrics’10, ICPE’17, DSN’17, SRDS’19, and HPDC'19. She also served as the General co-Chair of QEST’10 and NSMC’10. She is an ACM Distinguished Scientist.
---------------------------------------------------------------------------------------------------------------
Dr N. Muralidaran has over 30+ years of experience as an Information Technology professional in the Financial Services sector. He has a rich experience in building organizations. He has always been result oriented and a great team builder. His positive outlook has helped him in visualizing success in every opportunity that has come his way. In his last assignment as the Chief of Special Projects – NSEIL, he was responsible for the International Business Development and Exchange collaborations, strategic and futuristic technology and new initiatives of the exchange. Prior to this, as CEO of NSE Infotech Services Ltd., the captive IT services unit of NSE, he was responsible for the IT strategy, planning, software development and IT services of the exchange. Before joining the NSE group in 2004, he was the CEO / CTO with the IL&FS group since 1990. In this role he was responsible for strategy planning, design and implementation of IT solutions across different group companies. During this tenure, he was part of the initial core team involved in setting up the National Stock Exchange from conceptualization stage till the initial implementation. He continued to be a part of the exchange in an advisory capacity in different committees. He has also worked with Bhabha Atomic Research Centre (BARC) in the Reactor Analysis and Simulation Systems group and NELCO Ltd in the past.Dr N. Muralidaran holds a Ph.D. from Birla Institute of Technology, Mesra for his work in "Architecture Model for Scaling Mission Critical Real Time Applications for High Performance" - under the management stream. He also holds a PG Diploma in Computer Management and MBA in Finance.
This year's main theme is "performance engineering in the Artificial Intelligence era." We are looking for contributions that use AI techniques to enhance the performance modeling, estimation, and optimization of complex systems. At the same time we are looking for contributions that analyze and improve AI systems.
Topics of interest include, but are not limited to:
Performance modeling of software
* Languages and ontologies
* Methods and tools
* Relationship/integration/tradeoffs with other QoS attributes
* Analytical, simulation and statistical modeling methodologies
* Machine learning and neural networks
* Model validation and calibration techniques
* Automatic model extraction
* Performance modeling and analysis tools
Performance and software development processes/paradigms
* Software performance patterns and anti-patterns
* Software/performance tool interoperability (models and data interchange formats)
* Performance-oriented design, implementation and configuration
management
* Software Performance Engineering and Model-Driven Development
* Gathering, interpreting and exploiting software performance
annotations and data
* System sizing and capacity planning techniques
* (Model-driven) Performance requirements engineering
* Relationship between performance and architecture
* Collaboration of development and operation (DevOps) for performance
* Performance and agile methods
* Performance in Service-Oriented Architectures (SOA)
* Performance of microservice architectures and containers
* DevOps and Performance
Performance measurement, monitoring and analysis
* Performance measurement and monitoring techniques
* Analysis of measured application performance data
* Application tracing and profiling
* Workload characterization techniques
* Experimental design
* Tools for performance testing, measurement, profiling and tuning
Benchmarking
* Performance metrics and benchmark suites
* Benchmarking methodologies
* Development of parameterizable, flexible benchmarks
* Benchmark workloads and scenarios
* Use of benchmarks in industry and academia
Run-time performance management and adaptation
* Machine learning and runtime performance decisions
* Context modeling and analysis
* Runtime model estimation
* Use of models at run-time
* Online performance prediction
* Autonomic resource management
* Utility-based optimization
* Capacity management
Power and performance, energy efficiency
* Power consumption models and management techniques
* Tradeoffs between performance and energy efficiency
* Performance-driven resource and power management
Performance modeling and evaluation in different environments and application domains
* Web-based systems, e-business, Web services
* Big data systems and data analytics
* Deep-learning systems systems
* Internet of Things
* Social networks
* Cyber-physical systems
* Industrial Internet (Industry 4.0)
* Blockchain
* Virtualization and cloud computing
* Autonomous/adaptive systems
* Transaction-oriented systems
* Communication networks
* Parallel and distributed systems
* Embedded systems
* Multi-core systems
* Cluster and grid computing environments
* High performance computing
* Event-based systems
* Real-time and multimedia systems
* Low-latency systems
* Peer-to-peer, mobile and wireless systems
All other topics related to performance of software and systems.