2011.bib
@inproceedings{Br2011-SEDoktoranden-Symposium,
abstract = {{Today's enterprise systems based on increasingly complex software architectures often exhibit poor performance and resource efficiency thus having high operating costs. This is due to the inability to predict at run-time the effect of changes in the system environment and adapt the system accordingly. We propose a new performance modeling approach that allows the prediction of performance and system resource utilization online during system operation. We use architecture-level performance models that capture the performance-relevant information of the software architecture, deployment, execution environment and workload. The models will be automatically maintained during operation. To derive performance predictions, we propose a tailorable model solving approach to provide flexibility in view of prediction accuracy and analysis overhead.}},
address = {Bonn, Germany},
author = {Fabian Brosig},
bibsource = {DBLP, http://dblp.uni-trier.de},
booktitle = {Software Engineering (Workshops) - Doctoral Symposium, February 21--25, 2011},
editor = {Ralf Reussner and Alexander Pretschner and Stefan J{\"a}hnichen},
ee = {http://subs.emis.de/LNI/Proceedings/Proceedings184/article6310.html},
month = {February},
pages = {279--284},
pdf = {http://sdqweb.ipd.kit.edu/publications/descartes-pdfs/Br2011-SE-Symposium.pdf},
publisher = {GI},
series = {Lecture Notes in Informatics (LNI)},
title = {Online Performance Prediction with Architecture-Level Performance Models},
volume = {184},
year = {2011}
}
@inproceedings{BrHuKo2011-ASE-AutomExtraction,
abstract = {Modern service-oriented enterprise systems have increasingly complex and dynamic loosely-coupled architectures that often exhibit poor performance and resource efficiency and have high operating costs. This is due to the inability to predict at run-time the effect of dynamic changes in the system environment and adapt the system configuration accordingly. Architecture-level performance models provide a powerful tool for performance prediction, however, current approaches to modeling the execution context of software components are not suitable for use at run-time. In this paper, we analyze the typical online performance prediction scenarios and propose a novel performance meta-model for expressing and resolving parameter and context dependencies, specifically designed for use in online scenarios. We motivate and validate our approach in the context of a realistic and representative online performance prediction scenario based on the SPECjEnterprise2010 standard benchmark.},
address = {Oread, Lawrence, Kansas},
author = {Fabian Brosig and Nikolaus Huber and Samuel Kounev},
booktitle = {26th IEEE/ACM International Conference On Automated Software Engineering (ASE 2011)},
month = {November},
note = {Acceptance Rate (Full Paper): 14.7\% (37/252)},
pdf = {http://sdqweb.ipd.kit.edu/publications/descartes-pdfs/BrHuKo2011-ASE-AutomExtraction.pdf},
title = {{A}utomated {E}xtraction of {A}rchitecture-{L}evel {P}erformance {M}odels of {D}istributed {C}omponent-{B}ased {S}ystems},
year = {2011}
}
@inproceedings{Westermann2011b,
author = {Dennis, Westermann and Rouven, Krebs and Jens, Happe},
booktitle = {Proceedings of the Computer Performance Engineering - 8th European Performance Engineering Workshop (EPEW 2011)},
day = {12--13},
location = {Borrowdale, UK},
month = {October},
pages = {325-339},
pdf = {http://sdqweb.ipd.kit.edu/publications/pdfs/Westermann2011b.pdf},
publisher = {Springer},
title = {{E}fficient {E}xperiment {S}election in {A}utomated {S}oftware {P}erformance {E}valuations},
year = {2011}
}
@mastersthesis{Fa2011-KIT-SPAusingML,
address = {Karlsruhe, Germany},
author = {Michael Faber},
month = {March},
school = {Karlsruhe Institute of Technology (KIT)},
title = {{Software Performance Analysis using Machine Learning Techniques}},
year = {2011}
}
@inproceedings{hauck2011b,
address = {New York, NY, USA},
author = {Michael Hauck and Michael Kuperberg and Nikolaus Huber and Ralf Reussner},
booktitle = {Proceedings of the 7th ACM SIGSOFT International Conference on the Quality of Software Architectures (QoSA 2011)},
day = {20--24},
doi = {http://doi.acm.org/10.1145/2000259.2000269},
isbn = {978-1-4503-0724-6},
month = {June},
numpages = {10},
pages = {53--62},
pdf = {http://sdqweb.ipd.kit.edu/publications/pdfs/hauck2011b.pdf},
publisher = {ACM},
title = {{Ginpex: Deriving Performance-relevant Infrastructure Properties Through Goal-oriented Experiments}},
url = {10.1145/2000259.2000269},
year = {2011}
}
@mastersthesis{Herbst2011a,
abstract = {{Elasticity is the ability of a software system to dynamically adapt the amount of the resources it provides to clients as their workloads increase or decrease. In the context of cloud computing, automated resizing of a virtual machine's resources can be considered as a key step towards optimisation of a system's cost and energy efficiency. Existing work on cloud computing is limited to the technical view of implementing elastic systems, and definitions of scalability have not been extended to cover elasticity. This study thesis presents a detailed discussion of elasticity, proposes metrics as well as measurement techniques, and outlines next steps for enabling comparisons between cloud computing offerings on the basis of elasticity. I discuss results of our work on measuring elasticity of thread pools provided by the Java virtual machine, as well as an experiment setup for elastic CPU time slice resizing in a virtualized environment. An experiment setup is presented as future work for dynamically adding and removing z/VM Linux virtual machine instances to a performance relevant group of virtualized servers.}},
address = {Am Fasanengarten 5, 76131 Karlsruhe, Germany},
author = {Nikolas Roman Herbst},
keywords = {Cloud, Resource Elasticity},
pdf = {http://sdqweb.ipd.kit.edu/publications/pdfs/Herbst2011a.pdf},
school = {{Karlsruhe Institute of Technology (KIT)}},
title = {{Quantifying the Impact of Configuration Space for Elasticity Benchmarking}},
type = {{Study Thesis}},
year = {2011}
}
@inproceedings{HuBrKo2011-SEAMS-ResAlloc,
abstract = {The adoption of virtualization and Cloud Computing technologies promises a number of benefits such as increased flexibility, better energy efficiency and lower operating costs for IT systems. However, highly variable workloads make it challenging to provide quality-of-service guarantees while at the same time ensuring efficient resource utilization. To avoid violations of service-level agreements (SLAs) or inefficient resource usage, resource allocations have to be adapted continuously during operation to reflect changes in application workloads. In this paper, we present a novel approach to self-adaptive resource allocation in virtualized environments based on online architecture-level performance models. We present a detailed case study of a representative enterprise application, the new SPECjEnterprise2010 benchmark, deployed in a virtualized cluster environment. The case study serves as a proof-of-concept demonstrating the effectiveness and practical applicability of our approach.},
address = {New York, NY, USA},
author = {Nikolaus Huber and Fabian Brosig and Samuel Kounev},
booktitle = {6th International Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS 2011)},
day = {23--24},
doi = {10.1145/1988008.1988021},
isbn = {978-1-4503-0575-4},
location = {Waikiki, Honolulu, HI, USA},
month = {May},
note = {Acceptance Rate (Full Paper): 27\% (21/76)},
pages = {90--99},
pdf = {http://sdqweb.ipd.kit.edu/publications/descartes-pdfs/HuBrKo2011-SEAMS-ResAlloc.pdf},
publisher = {ACM},
title = {{Model-based Self-Adaptive Resource Allocation in Virtualized Environments}},
url = {http://dl.acm.org/authorize?425581},
year = {2011}
}
@inproceedings{HuQuHaKo2011-CLOSER-ModelVirtOverhead,
abstract = {Due to trends like Cloud Computing and Green IT, virtualization technologies are gaining increasing importance. They promise energy and cost savings by sharing physical resources, thus making resource usage more efficient. However, resource sharing and other factors have direct effects on system performance, which are not yet well-understood. Hence, performance prediction and performance management of services deployed in virtualized environments like public and private Clouds is a challenging task. Because of the large variety of virtualization solutions, a generic approach to predict the performance overhead of services running on virtualization platforms is highly desirable. In this paper, we present experimental results on two popular state-of-the-art virtualization platforms, Citrix XenServer 5.5 and VMware ESX 4.0, as representatives of the two major hypervisor architectures. Based on these results, we propose a basic, generic performance prediction model for the two different types of hypervisor architectures. The target is to predict the performance overhead for executing services on virtualized platforms.},
author = {Nikolaus Huber and Marcel von Quast and Michael Hauck and Samuel Kounev},
booktitle = {Proceedings of the 1st International Conference on Cloud Computing and Services Science (CLOSER 2011)},
day = {7--9},
http = {http://closer.scitevents.org/},
isbn = {978-989-8425-52-2},
location = {Noordwijkerhout, The Netherlands},
month = {May},
note = {Acceptance Rate: 18/164 = 10.9\%, Best Paper Award},
pages = {563 -- 573},
pdf = {http://sdqweb.ipd.kit.edu/publications/descartes-pdfs/HuQuHaKo2011-CLOSER-ModelVirtOverhead.pdf},
publisher = {SciTePress},
title = {{E}valuating and {M}odeling {V}irtualization {P}erformance {O}verhead for {C}loud {E}nvironments},
year = {2011}
}
@inproceedings{klatt2011a,
abstract = {With the introduction of services, software systems have become more flexible as new services can easily be composed from existing ones. Service composition frameworks offer corresponding functionality and hide the complexity of the underlying technologies from their users. However, possibilities for anticipating quality properties of com- posed services before their actual operation are limited so far. While existing approaches for model-based software quality prediction can be used by service composers for determining realizable Quality of Service (QoS) levels, integration of such techniques into composition frameworks is still missing. As a result, high effort and expert knowledge is required to build the system models required for prediction. In this paper, we present a novel service composition process that includes QoS prediction for composed services as an integral part. Furthermore, we describe how composition frameworks can be extended to support this process. With our approach, systematic consideration of service quality during the composition process is naturally achieved, without the need for de- tailed knowledge about the underlying prediction models. To evaluate our work and validate its applicability in different domains, we have integrated QoS prediction support according to our process in two com- position frameworks -- a large-scale SLA management framework and a service mashup platform.},
author = {Benjamin Klatt and Franz Brosch and Zoya Durdik and Christoph Rathfelder},
booktitle = {5th Workshop on Non-Functional Properties and SLA Management in Service-Oriented Computing (NFPSLAM-SOC 2011)},
day = {5--8},
location = {Paphos, Cyprus},
month = {December},
pdf = {http://sdqweb.ipd.kit.edu/publications/pdfs/klatt2011a.pdf},
title = {{Quality Prediction in Service Composition Frameworks}},
year = {2011}
}
@inproceedings{KlRaKo2011-QoSA-PCMEvents,
abstract = {Today, software engineering is challenged to handle more and more large-scale distributed systems with guaranteed quality-of-service. Component-based architectures have been established to build such systems in a more structured and manageable way. Modern architectures often utilize event-based communication which enables loosely-coupled interactions between components and leads to improved system scalability. However, the loose coupling of components makes it challenging to model such architectures in order to predict their quality properties, e.g., performance and reliability, at system design time. In this paper, we present an extension of the Palladio Component Model (PCM) and the Palladio software quality prediction framework, enabling the modeling of event-based communication in component-based architectures. The contributions include: i) a meta-model extension supporting events as first class entities, ii) a model-to-model transformation from the extended to the original PCM, iii) an integration of the transformation into the Palladio tool chain allowing to use existing model solution techniques, and iv) a detailed evaluation of the reduction of the modeling effort enabled by the transformation in the context of a real-world case study.},
address = {New York, NY, USA},
author = {Klatt, Benjamin and Rathfelder, Christoph and Kounev, Samuel},
booktitle = {Proceedings of the joint ACM SIGSOFT conference -- QoSA and ACM SIGSOFT symposium -- ISARCS on Quality of software architectures -- QoSA and architecting critical systems -- ISARCS (QoSA-ISARCS 2011)},
day = {20--24},
doi = {http://doi.acm.org/10.1145/2000259.2000268},
isbn = {978-1-4503-0724-6},
keywords = {component-based architectures, event-based communication, performance prediction},
location = {Boulder, Colorado, USA},
month = {June},
numpages = {10},
organization = {SIGSOFT},
pages = {43--52},
pdf = {http://sdqweb.ipd.kit.edu/publications/pdfs/KlRaKo2011-QoSA-PCMEvents.pdf},
publisher = {ACM},
title = {Integration of event-based communication in the palladio software quality prediction framework},
url = {http://doi.acm.org/10.1145/2000259.2000268},
year = {2011}
}
@inproceedings{Ko2011-BMSD-PerfEngOfBis,
author = {Samuel Kounev},
booktitle = {International Symposium on Business Modeling and Software Design (BMSD 2011), Sofia, Bulgaria, July 27--28, 2011},
isbn = {978-989-8425-68-3},
month = {July},
pdf = {http://sdqweb.ipd.kit.edu/publications/descartes-pdfs/Ko2011-BMSD-EvSPE.pdf},
title = {{Performance Engineering of Business Information Systems - Filling the Gap between High-level Business Services and Low-level Performance Models}},
year = {2011}
}
@inproceedings{Ko2011-EPEW-ResearchChallenges,
author = {Samuel Kounev},
booktitle = {Proceedings of the 8th European Performance Engineering Workshop (EPEW'11), Borrowdale, The English Lake District, October 12--13},
note = {(Keynote Talk)},
pdf = {http://sdqweb.ipd.kit.edu/publications/descartes-pdfs/Ko2011-EPEW-Keynote.pdf},
title = {{Engineering of Self-Aware IT Systems and Services: State-of-the-Art and Research Challenges}},
year = {2011}
}
@inproceedings{Ko2011-SE-DescartesResearch,
address = {Karlsruhe, Germany},
author = {Samuel Kounev},
booktitle = {{GI Softwaretechnik-Trends, 31(4), November 2011, ISSN 0720-8928}},
pdf = {http://sdqweb.ipd.kit.edu/publications/descartes-pdfs/Ko2011-SE-DescartesResearch.pdf},
title = {{Self-Aware Software and Systems Engineering: A Vision and Research Roadmap}},
url = {http://pi.informatik.uni-siegen.de/stt/31_4/index.html},
year = {2011}
}
@inproceedings{KoBeBrHuOk2011-SIMUTools-DataFabrics,
abstract = {Enterprise data fabrics are gaining increasing attention in many industry domains including financial services, telecommunications, transportation and health care. Providing a distributed, operational data platform sitting between application infrastructures and back-end data sources, enterprise data fabrics are designed for high performance and scalability. However, given the dynamics of modern applications, system sizing and capacity planning need to be done continuously during operation to ensure adequate quality-of-service and efficient resource utilization. While most products are shipped with performance monitoring and analysis tools, such tools are typically focused on low-level profiling and they lack support for performance prediction and capacity planning. In this paper, we present a novel case study of a representative enterprise data fabric, the GemFire EDF, presenting a simulation-based tool that we have developed for automated performance prediction and capacity planning. The tool, called Jewel, automates resource demand estimation, performance model generation, performance model analysis and results processing. We present an experimental evaluation of the tool demonstrating its effctiveness and practical applicability.},
address = {Brussels, Belgium, Belgium},
author = {Samuel Kounev and Konstantin Bender and Fabian Brosig and Nikolaus Huber and Russell Okamoto},
booktitle = {4th International ICST Conference on Simulation Tools and Techniques},
day = {21--25},
isbn = {978-1-936968-00-8},
location = {Barcelona, Spain},
month = {March},
note = {Acceptance Rate (Full Paper): 29.8\% (23/77), ICST Best Paper Award},
pages = {27--36},
pdf = {http://sdqweb.ipd.kit.edu/publications/descartes-pdfs/KoBeBrHuOk2011-ICST-DataFabrics.pdf},
publisher = {ICST},
slides = {http://sdqweb.ipd.kit.edu/publications/descartes-pdfs/KoBeBrHuOk2011-ICST-DataFabrics_Slides.pdf},
title = {{Automated Simulation-Based Capacity Planning for Enterprise Data Fabrics}},
year = {2011}
}
@inproceedings{KoBrHu2011-ICAC-QoSManagement,
abstract = {We present an overview of our work-in-progress and long-term research agenda aiming to develop a novel methodology for engineering of self-aware software systems. The latter will have built-in architecture-level QoS models enhanced to capture dynamic aspects of the system environment and maintained automatically during operation. The models will be exploited at run-time to adapt the system to changes in the environment ensuring that resources are utilized efficiently and QoS requirements are satisfied.},
author = {Samuel Kounev and Fabian Brosig and Nikolaus Huber},
booktitle = {8th International Conference on Autonomic Computing (ICAC 2011)},
day = {14--18},
location = {Karlsruhe, Germany},
month = {June},
pdf = {http://sdqweb.ipd.kit.edu/publications/descartes-pdfs/KoBrHu2011-ICAC-QoSManagement.pdf},
title = {{Self-Aware QoS Management in Virtualized Infrastructures (Poster Paper)}},
year = {2011}
}
@manual{KoSp2011-QPME20-UserGuide,
address = {Am Fasanengarten 5, 76131 Karlsruhe, Germany},
author = {Samuel Kounev and Simon Spinner},
month = {May},
organization = {Karlsruhe Institute of Technology},
pdf = {http://descartes.ipd.kit.edu/fileadmin/user_upload/descartes/QPME/QPME-UsersGuide.pdf},
title = {{QPME 2.0 User's Guide}},
url = {http://descartes.ipd.kit.edu/projects/qpme/},
year = {2011}
}
@inproceedings{koziolek2011b,
abstract = {Quantitative prediction of non-functional properties, such as performance, reliability, and costs, of software architectures supports systematic software engineering. Even though there usually is a rough idea on bounds for quality of service, the exact required values may be unclear and subject to trade-offs. Designing architectures that exhibit such good trade-off between multiple quality attributes is hard. Even with a given functional design, many degrees of freedom in the software architecture (e.g. component deployment or server configuration) span a large design space. Automated approaches search the design space with multi-objective metaheuristics such as evolutionary algorithms. However, as quality prediction for a single architecture is computationally expensive, these approaches are time consuming. In this work, we enhance an automated improvement approach to take into account bounds for quality of service in order to focus the search on interesting regions of the objective space, while still allowing trade-offs after the search. We compare two different constraint handling techniques to consider the bounds. To validate our approach, we applied both techniques to an architecture model of a component-based business information system. We compared both techniques to an unbounded search in 4 scenarios. Every scenario was examined with 10 optimization runs, each investigating around 1600 architectural candidates. The results indicate that the integration of quality of service bounds during the optimization process can improve the quality of the solutions found, however, the effect depends on the scenario, i.e. the problem and the quality requirements. The best results were achieved for costs requirements: The approach was able to decrease the time needed to find good solutions in the interesting regions of the objective space by 25\% on average.},
author = {Anne Koziolek and Qais Noorshams and Ralf Reussner},
booktitle = {{Models in Software Engineering, Workshops and Symposia at MODELS 2010, Oslo, Norway, October 3-8, 2010, Reports and Revised Selected Papers}},
doi = {10.1007/978-3-642-21210-9_37},
editor = {J. Dingel and A. Solberg},
pages = {384--399},
pdf = {http://sdqweb.ipd.uka.de/publications/pdfs/koziolek2011b.pdf},
publisher = {Springer-Verlag Berlin Heidelberg},
series = {Lecture Notes in Computer Science},
title = {Focussing Multi-objective Software Architecture Optimization Using Quality of Service Bounds},
url = {http://dx.doi.org/10.1007/978-3-642-21210-9},
volume = {6627},
year = {2011}
}
@techreport{KuHeKiRe2011-ResourceElasticity,
abstract = {{Elasticity is the ability of a software system to dynamically scale the amount of the resources it provides to clients as their workloads increase or decrease. Elasticity is praised as a key advantage of cloud computing, where computing resources are dynamically added and released. However, there exists no concise or formal definition of elasticity, and thus no approaches to quantify it have been developed so far. Existing work on cloud computing is limited to the technical view of implementing elastic systems, and definitions or scalability have not been extended to cover elasticity. In this report, we present a detailed discussion of elasticity, propose techniques for quantifying and measuring it, and outline next steps to be taken for enabling comparisons between cloud computing offerings on the basis of elasticity. We also present preliminary work on measuring elasticity of resource pools provided by the Java Virtual Machine.}},
address = {Am Fasanengarten 5, 76131 Karlsruhe, Germany},
author = {Michael Kuperberg and Nikolas Roman Herbst and Joakim Gunnarson von Kistowski and Ralf Reussner},
institution = {Karlsruhe Institute of Technology (KIT)},
issn = {2190-4782},
pdf = {http://sdqweb.ipd.kit.edu/publications/pdfs/KuHeKiRe2011-ResourceElasticity.pdf},
series = {Karlsruhe Reports in Informatics},
title = {{Defining and Quantifying Elasticity of Resources in Cloud Computing and Scalable Platforms}},
url = {http://digbib.ubka.uni-karlsruhe.de/volltexte/1000023476},
volume = {16},
year = {2011}
}
@inproceedings{MeKoKo2011-MASCOTS-PCMtoQPN,
author = {Philipp Meier and Samuel Kounev and Heiko Koziolek},
booktitle = {19th IEEE/ACM International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems (MASCOTS 2011), Singapore, July 25--27},
note = {Acceptance Rate (Full Paper): 41/157 = 26\%},
pdf = {http://sdqweb.ipd.kit.edu/publications/descartes-pdfs/MeKoKo2011-MASCOTS-PCMtoQPN.pdf},
title = {{Automated Transformation of Component-based Software Architecture Models to Queueing Petri Nets}},
year = {2011}
}
@inproceedings{MoKr2011-esosym-qualitative-discussion,
address = {Bonn-Buschdorf, Germany},
author = {Momm, Christof and Krebs, Rouven},
booktitle = {Proceedings of the Software Engineering 2011 -- Workshopband (ESoSyM-2011)},
day = {21},
editor = {Reussner, Ralf and Pretschner, Alexander amd J{\"a}hnichen, Stefan},
isbn = {978-3-88579-278-9},
location = {Karlsruhe, Germany},
month = {February},
organization = {Fachgruppe OOSE der Gesellschaft f{\"u}r Informatik und ihrer Arbeitskreise},
pages = {139--150},
pdf = {http://sdqweb.ipd.kit.edu/publications/pdfs/MoKr2011-esosym-qualitative-discussion.pdf},
publisher = {Bonner K\"ollen Verlag},
title = {{A} {Q}ualitative {D}iscussion of {D}ifferent {A}pproaches for {I}mplementing {M}ulti-{T}enant {S}aa{S} {O}fferings},
titleaddon = {Short Paper},
year = {2011}
}
@inproceedings{rathfelder2011a,
abstract = {Today, software engineering is challenged to handle more and more large-scale distributed systems with a guaranteed level of service quality. Component-based architectures have been established to build more structured and manageable software systems. However, due to time and cost constraints, it is not feasible to use a trial and error approach to ensure that an architecture meets the quality of service (QoS) requirements. In this tool demo, we present the Palladio Workbench that permits the modeling of component-based software architectures and the prediction of its quality characteristics (e.g., response time and utilization). Additional to a general tool overview, we will give some insights about a new feature to analyze the impact of event-driven communication that was added in the latest release of the Palladio Component Model (PCM)},
address = {Washington, DC, USA},
author = {Rathfelder, Christoph and Klatt, Benjamin},
booktitle = {Proceedings of the 2011 Ninth Working IEEE/IFIP Conference on Software Architecture (WICSA 2011)},
day = {20--24},
doi = {http://dx.doi.org/10.1109/WICSA.2011.55},
isbn = {978-0-7695-4351-2},
location = {Boulder, Colorado, USA},
month = {June},
pages = {347--350},
pdf = {http://sdqweb.ipd.kit.edu/publications/pdfs/rathfelder2011a.pdf},
publisher = {IEEE Computer Society},
title = {Palladio Workbench: A Quality-Prediction Tool for Component-Based Architectures},
url = {http://dx.doi.org/10.1109/WICSA.2011.55},
year = {2011}
}
@book{rathfelder2010c,
abstract = {With the introduction of services, systems become more flexible as new services can easily be composed out of existing services. Services are increasingly used in mission-critical systems and applications and therefore considering Quality of Service (QoS) properties is an essential part of the service selection. Quality prediction techniques support the service provider in determining possible QoS levels that can be guaranteed to a customer or in deriving the operation costs induced by a certain QoS level. In this chapter, we present an overview on our work on modeling service-oriented systems for performance prediction using the Palladio Component Model. The prediction builds upon a model of a service-based system, and evaluates this model in order to determine the expected service quality. The presented techniques allow for early quality prediction, without the need for the system being already deployed and operating. We present the integration of our prediction approach into an SLA management framework. The emerging trend to combine event-based communication and Service-Oriented Architecture (SOA) into Event-based SOA (ESOA) induces new challenges to our approach, which are topic of a special subsection.},
address = {Hershey, PA, USA},
author = {Christoph Rathfelder and Benjamin Klatt and Franz Brosch and Samuel Kounev},
booktitle = {{Handbook of Research on Service-Oriented Systems and Non-Functional Properties: Future Directions}},
doi = {10.4018/978-1-61350-432-1},
editor = {Stephan Reiff-Marganiec and Marcel Tilly},
isbn = {9781613504321},
month = {December},
pages = {258--279},
publisher = {IGI Global},
title = {{P}erformance {M}odeling for {Q}uality of {S}ervice {P}rediction in {S}ervice-{O}riented {S}ystems},
url = {http://www.igi-global.com/chapter/handbook-research-service-oriented-systems/60889},
year = {2011}
}
@book{rathfelder2011b,
address = {New York},
author = {Rathfelder, Christoph and Klatt, Benjamin and Falcone, Giovanni},
booktitle = {{Service Level Agreements for Cloud Computing}},
editor = {Wieder, Philipp and Butler, Joe M. and Theilmann, Wolfgang and Yahyapour, Ramin},
isbn = {978-1-4614-1614-2},
pages = {27--40},
publisher = {Springer},
title = {The Open Reference Case A Reference Use Case for the SLA@SOI Framework},
url = {http://dx.doi.org/10.1007/978-1-4614-1614-2_3},
year = {2011}
}
@inproceedings{RaKoEv2011-ASE-CapacityPlanning,
abstract = {Event-based communication is used in different domains including telecommunications, transportation, and business information systems to build scalable distributed systems. The loose coupling of components in such systems makes it easy to vary the deployment. At the same time, the complexity to estimate the behavior and performance of the whole system is increased, which complicates capacity planning. In this paper, we present an automated performance prediction method supporting capacity planning for event-based systems. The performance prediction is based on an extended version of the Palladio Component Model -- a performance meta-model for component-based systems. We apply this method on a real-world case study of a traffic monitoring system. In addition to the application of our performance prediction techniques for capacity planning, we evaluate the prediction results against measurements in the context of the case study. The results demonstrate the practicality and effectiveness of the proposed approach.},
author = {Christoph Rathfelder and Samuel Kounev and David Evans},
booktitle = {26th IEEE/ACM International Conference On Automated Software Engineering (ASE 2011)},
day = {6--12},
location = {Oread, Lawrence, Kansas},
month = {November},
note = {Acceptance Rate (Full Paper): 14.7\% (37/252)},
pages = {352--361},
pdf = {http://sdqweb.ipd.kit.edu/publications/pdfs/RaKoEv2011-ASE-CapacityPlanning.pdf},
publisher = {IEEE},
title = {{C}apacity {P}lanning for {E}vent-based {S}ystems using {A}utomated {P}erformance {P}redictions},
year = {2011}
}
@mastersthesis{Spinner2011a,
address = {Am Fasanengarten 5, 76131 Karlsruhe, Germany},
author = {Simon Spinner},
month = {July},
note = {Best Graduate Award from the Faculty of Informatics},
pdf = {http://sdqweb.ipd.kit.edu/publications/pdfs/Spinner2011a.pdf},
school = {Karlsruhe Institute of Technology (KIT)},
title = {{Evaluating Approaches to Resource Demand Estimation}},
year = {2011}
}
@article{Thomas20111,
address = {Amsterdam, The Netherlands},
author = {Nigel Thomas and Jeremy Bradley and William Knottenbelt and Samuel Kounev and Nikolaus Huber and Fabian Brosig},
doi = {10.1016/j.entcs.2011.09.001},
issn = {1571-0661},
journal = {Electronic Notes in Theoretical Computer Science},
pages = {1 - 3},
publisher = {Elsevier Science Publishers B. V.},
title = {Preface},
volume = {275},
year = {2011}
}
@proceedings{DBLP:conf/wosp/2011,
address = {New York, NY, USA},
editor = {Samuel Kounev and Vittorio Cortellessa and Raffaela Mirandola and David J. Lilja},
isbn = {978-1-4503-0519-8},
month = {March},
publisher = {ACM},
title = {ICPE'11 - 2nd Joint ACM/SPEC International Conference on Performance Engineering, Karlsruhe, Germany, March 14--16, 2011},
year = {2011}
}