inproceedings_krebs.bib

@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}
}

@inproceedings{KrMoKo2012-QoSA-QuantifyingPerfIsoMetrics,
  address = {New York, USA},
  author = {Krebs, Rouven and Momm, Christof and Kounev, Samuel},
  booktitle = {Proceedings of the 8th ACM SIGSOFT International Conference on the Quality of Software Architectures (QoSA 2012)},
  day = {25--28},
  editor = {Buhnova, Barbora and Vallecillo, Antonio},
  location = {Bertinoro, Italy},
  month = {June},
  note = {Acceptance Rate (Full Paper): 25.6\%},
  pages = {91--100},
  pdf = {http://sdqweb.ipd.kit.edu/publications/pdfs/KrMoKo2012-QoSA-QuantifyingPerfIsoMetrics.pdf},
  publisher = {ACM Press},
  title = {{M}etrics and {T}echniques for {Q}uantifying {P}erformance {I}solation in {C}loud {E}nvironments},
  url = {http://qosa.ipd.kit.edu/qosa_2012/},
  year = {2012}
}

@inproceedings{KrMoKo2012-closer-multitenant-saas,
  author = {Krebs, Rouven and Momm, Christof and Kounev, Samuel},
  booktitle = {{Proceedings of the 2nd International Conference on Cloud Computing and Services Science (CLOSER 2012)}},
  day = {18--21},
  location = {Setubal, Portugal},
  month = {April},
  pdf = {http://sdqweb.ipd.kit.edu/publications/pdfs/KrMoKo2012-closer-multitenant-sass.pdf},
  publisher = {SciTePress},
  title = {{Architectural Concerns in Multi-Tenant SaaS Applications}},
  titleaddon = {(Short Paper)},
  year = {2012}
}

@inproceedings{KrWeKo2013-icwe-MTBenchmark,
  author = {Krebs, Rouven and Wert, Alexander and Kounev, Samuel},
  booktitle = {{Proceedings of the 13th International Conference on Web Engineering (ICWE 2013)}},
  day = {8--12},
  location = {Aalborg, Denmark},
  month = {July},
  organization = {Aalborg University, Denmark},
  pdf = {http://sdqweb.ipd.kit.edu/publications/pdfs/KrWeKo2013-icwe-MTBenchmark.pdf},
  publisher = {Springer-Verlag},
  title = {{Multi-Tenancy Performance Benchmark for Web Application Platforms}},
  titleaddon = {Industrial Track},
  year = {2013}
}

@inproceedings{LoKr2013-Closer-Isolation,
  author = {Loesch, Manuel and Krebs, Rouven},
  booktitle = {{Proceedings of the 3rd International Conference on Cloud Computing and Service Science (CLOSER 2013)}},
  day = {8--10},
  location = {Aachen, Germany},
  month = {May},
  organization = {RWTH Aachen, Germany},
  pdf = {http://sdqweb.ipd.kit.edu/publications/pdfs/LoKr2013-Closer-Isolation.pdf},
  publisher = {SciTePress},
  title = {{Conceptual Approach for Performance Isolation in Multi-Tenant Systems}},
  titleaddon = {Short Paper},
  year = {2013}
}

@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{westermann2012b,
  author = {Dennis Westermann and Jens Happe and Rouven Krebs and Roozbeh Farahbod},
  booktitle = {Proceedings of the 27th IEEE/ACM International Conference On Automated Software Engineering (ASE 2012)},
  day = {3--7},
  location = {Essen, Germany},
  month = {September},
  title = {Automated Inference of Goal-oriented Performance Prediction Functions},
  year = {2012}
}

@inproceedings{KrLoKo2013-CGC-PerformanceIsolationFramework,
  author = {Rouven Krebs and Manuel Loesch and Samuel Kounev},
  booktitle = {Proceedings of the 3rd IEEE International Conference on Cloud and Green Computing (CGC 2013)},
  location = {Karlsruhe, Germany},
  title = {{Performance Isolation Framework for Multi-Tenant Applications}},
  year = {2013}
}

@inproceedings{KrScHe2014-HotTopiCS-OptimizationApproach,
  abstract = {{Software-as-a-Service (SaaS) often shares one single application instance among different tenants to reduce costs. However, sharing potentially leads to undesired influence from one tenant onto the performance observed by the others. Furthermore, providing one tenant additional resources to support its increasing demands without increasing the performance of tenants who do not pay for it is a major challenge. The application intentionally does not manage hardware resources, and the OS is not aware of application level entities like tenants. Thus, it is difficult to control the performance of different tenants to keep them isolated. These problems gain importance as performance is one of the major obstacles for cloud customers. Existing work applies request based admission control mechanisms like a weighted round robin with an individual queue for each tenant to control the share guaranteed for a tenant. However, the computation of the concrete weights for such an admission control is still challenging. In this paper, we present a fitness function and optimization approach reflecting various requirements from this field to compute proper weights with the goal to ensure an isolated performance as foundation to scale on a tenants basis.}},
  author = {Rouven Krebs and Philipp Schneider and Nikolas Herbst},
  booktitle = {Proceedings of the 2nd International Workshop on Hot Topics in Cloud Service Scalability (HotTopiCS 2014), co-located with the 5th ACM/SPEC International Conference on Performance Engineering (ICPE 2014)},
  day = {22},
  keywords = {SaaS, Multi-Tenancy, Performance, Isolation, Scalability},
  location = {Dublin, Ireland},
  month = {March},
  pdf = {http://sdqweb.ipd.kit.edu/publications/pdfs/KrScHe2014-HotTopiCS-OptimizationApproach.pdf},
  publisher = {ACM},
  slides = {http://sdqweb.ipd.kit.edu/publications/pdfs/KrScHe2014-HotTopiCS-OptimizationApproach-Slides.pdf},
  title = {{Optimization Method for Request Admission Control to Guarantee Performance Isolation}},
  year = {2014}
}

@inproceedings{KrSpAhKo2014_CCGrid_ResourceIsolation,
  abstract = {{Multi-tenancy is an approach to share one application instance among multiple customers by providing each of them a dedicated view. This approach is commonly used by SaaS providers to reduce the costs for service provisioning. Tenants also expect to be isolated in terms of the performance they observe and the providers inability to offer performance guarantees is a major obstacle for potential cloud customers. To guarantee an isolated performance it is essential to control the resources used by a tenant. This is a challenge, because the layers of the execution environment, responsible for controlling resource usage (e.g., operating system), normally do not have knowledge about entities defined at the application level and thus they cannot distinguish between different tenants. Furthermore, it is hard to predict how tenant requests propagate through the multiple layers of the execution environment down to the physical resource layer. The intended abstraction of the application from the resource controlling layers does not allow to solely solving this problem in the application. In this paper, we propose an approach which applies resource demand estimation techniques in combination with a request based admission control. The resource demand estimation is used to determine resource consumption information for individual requests. The admission control mechanism uses this knowledge to delay requests originating from tenants that exceed their allocated resource share. The proposed method is validated by a widely accepted benchmark showing its applicability in a setup motivated by today's platform environments.}},
  author = {Rouven Krebs and Simon Spinner and Nadia Ahmed and Samuel Kounev},
  booktitle = {Proceedings of the 14th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid 2014)},
  day = {26},
  location = {Chicago, IL, USA},
  month = {May},
  note = {Accepted for Publication},
  pdf = {http://sdqweb.ipd.kit.edu/publications/pdfs/KrSpAhKo2014_CCGrid_ResourceIsolation.pdf},
  publisher = {IEEE/ACM},
  title = {{Resource Usage Control In Multi-Tenant Applications}},
  year = {2014}
}

@inproceedings{KrLo2014_Closer_IsolationTypes,
  abstract = {{Multi-tenancy is an approach to share one application instance among multiple customers by providing each of them a dedicated view. This approach is commonly used by SaaS providers to reduce the costs for service provisioning. Tenants also expect to be isolated in terms of the performance they observe and the providers inability to offer performance guarantees is a major obstacle for potential cloud customers. To guarantee an isolated performance it is essential to control the resources used by a tenant. This is a challenge, because the layers of the execution environment, responsible for controlling resource usage (e.g., operating system), normally do not have knowledge about entities defined at the application level and thus they cannot distinguish between different tenants. Furthermore, it is hard to predict how tenant requests propagate through the multiple layers of the execution environment down to the physical resource layer. The intended abstraction of the application from the resource controlling layers does not allow to solely solving this problem in the application. In this paper, we propose an approach which applies resource demand estimation techniques in combination with a request based admission control. The resource demand estimation is used to determine resource consumption information for individual requests. The admission control mechanism uses this knowledge to delay requests originating from tenants that exceed their allocated resource share. The proposed method is validated by a widely accepted benchmark showing its applicability in a setup motivated by today's platform environments.}},
  author = {Rouven Krebs and Manuel Loesch},
  booktitle = {Proceedings of 4th International Conference On Cloud Computing And Services Science (CLOSER 2014)},
  day = {3},
  location = {Barcelona, Spain},
  month = {April},
  note = {Short Paper},
  pdf = {http://sdqweb.ipd.kit.edu/publications/pdfs/KrLo2014_Closer_IsolationTypes.pdf},
  publisher = {SciTePress},
  title = {{Comparison of Request Admission Based Performance Isolation Approaches in Multi-Tenant SaaS Applications}},
  year = {2014}
}