PESOS '13: "Towards QoS Prediction Based ..."
Towards QoS Prediction Based on Composition Structure Analysis and Probabilistic Environment Models
Dragan Ivanović, Peerachai Kaowichakorn, and Manuel Carro
(UPM, Spain; IMDEA Software Institute, Spain)
Complex software systems are usually built by composing numerous components, including external services. The quality of service (QoS) is essential for determining the usability of such systems, and depends both on the structure of the composition and on the QoS of its components. Since the QoS of each component is usually determined with uncertainty and varies from one invocation to another, the composite system also exhibits stochastic QoS behavior. We propose an approach for computing probability distributions of the composite system QoS attributes based on known probability distributions of the component QoS attributes and the composition structure. The approach is experimentally evaluated using a prototype analyzer tool and a real-world service-based example, by comparing the predicted probability distributions for the composition QoS with the actual distribution of QoS values from repeated actual executions.
@InProceedings{PESOS13p11,
author = {Dragan Ivanović and Peerachai Kaowichakorn and Manuel Carro},
title = {Towards QoS Prediction Based on Composition Structure Analysis and Probabilistic Environment Models},
booktitle = {Proc.\ PESOS},
publisher = {IEEE},
pages = {11--20},
doi = {},
year = {2013},
}
PESOS '13: "Storm Prediction in a Cloud ..."
Storm Prediction in a Cloud
Ian Davis, Hadi Hemmati, Richard C. Holt, Michael W. Godfrey, Douglas Neuse, and Serge Mankovskii
(University of Waterloo, Canada; CA Technologies, USA)
Predicting future behavior reliably and efficiently is key for systems that manage virtual services; such systems must be able to balance loads within a cloud environment to ensure that service level agreements are met at a reasonable expense. In principle accurate predictions can be achieved by mining a variety of data sources, which describe the historic behavior of the services, the requirements of the programs running on them, and the evolving demands placed on the cloud by end users. Of particular importance is accurate prediction of maximal loads likely to be observed in the short term. However, standard approaches to modeling system behavior, by analyzing the totality of the observed data, tend to predict average rather than exceptional system behavior and ignore important patterns of change over time. In this paper, we study the ability of a simple multivariate linear regression for forecasting of peak CPU utilization (storm) in an industrial cloud environment. We also propose several modifications to the standard linear regression to adjust it for storm prediction.
@InProceedings{PESOS13p37,
author = {Ian Davis and Hadi Hemmati and Richard C. Holt and Michael W. Godfrey and Douglas Neuse and Serge Mankovskii},
title = {Storm Prediction in a Cloud},
booktitle = {Proc.\ PESOS},
publisher = {IEEE},
pages = {37--40},
doi = {},
year = {2013},
}
PESOS '13: "Dynamic Program Code Distribution ..."
Dynamic Program Code Distribution in Infrastructure-as-a-Service Clouds
Rostyslav Zabolotnyi, Philipp Leitner, and Schahram Dustdar
(TU Vienna, Austria)
Elastically scaling cloud computing applications are becoming more and more prevalent in today's IT landscapes. One problem of building such applications in an Infrastructure-as-a-Service cloud is the runtime distribution of program code, configuration files and other resources. While it is possible to include all required program code in the used IaaS base images, this severely restricts the achievable dynamicity at runtime. In this paper, we present a framework for dynamic program code distribution. Our approach handles code distribution entirely transparently on middleware layer. We base our solution on an existing middleware, CloudScale. The paper discusses the design and implementation of our code distribution approach on top of CloudScale, and numerically evaluates the practicability and performance of the approach based on an illustrative case study.
@InProceedings{PESOS13p29,
author = {Rostyslav Zabolotnyi and Philipp Leitner and Schahram Dustdar},
title = {Dynamic Program Code Distribution in Infrastructure-as-a-Service Clouds},
booktitle = {Proc.\ PESOS},
publisher = {IEEE},
pages = {29--36},
doi = {},
year = {2013},
}
PESOS '13: "The Dark Side of SOA Testing: ..."
The Dark Side of SOA Testing: Towards Testing Contemporary SOAs Based on Criticality Metrics
Philipp Leitner, Stefan Schulte, Schahram Dustdar, Ingo Pill, Marco Schulz, and Franz Wotawa
(TU Vienna, Austria; TU Graz, Austria)
Service-Oriented Architectures (SOAs) have widely been accepted as the standard way of building large-scale, heterogeneous enterprise IT systems. In this paper, we explore the current limitations of testing contemporary SOAs, which are typically assemblies of various components, including services, message buses, business processes, and support components. We argue that, currently, SOA testing is too much concerned with testing single services or business processes, while there is little scientific literature on holistic testing of contemporary SOAs that includes all critical components and their mutual dependencies and interactions. In this paper, we detail the architecture of contemporary SOA, thoroughly assess the current state of research in respect of their testing, and introduce the notion of SOA criticality metrics as indicators for an individual component's criticality for the SOA as a whole. We enumerate an initial metric set for various component types and interactions, as well as discuss how these metrics can be used for testing contemporary SOA.
@InProceedings{PESOS13p45,
author = {Philipp Leitner and Stefan Schulte and Schahram Dustdar and Ingo Pill and Marco Schulz and Franz Wotawa},
title = {The Dark Side of SOA Testing: Towards Testing Contemporary SOAs Based on Criticality Metrics},
booktitle = {Proc.\ PESOS},
publisher = {IEEE},
pages = {45--53},
doi = {},
year = {2013},
}
PESOS '13: "Building Reliable Dynamic ..."
Building Reliable Dynamic Applications for Ubiquitous Computing
Jacky Estublier and German Vega
(LIG, France; Grenoble University, France)
Service platforms emphasize dynamism and flexibility, at the cost of very little control over applications execution. Indeed, service platforms like OSGi do not provide an application concept or any structuring concept; they only support a flat space of services and a low-level run-time protocol. This was acceptable because, so far, a single application made of well-known services was running inside a platform. This was convenient because, in ubiquitous and dynamic environments, the available services and their dynamic behavior are not known in advance, eliminating the possibility to define an application by the list of its components. In the near future, service platform will support many shared services from independent providers and many applications managing critical services, like home security applications. Although, in this context, the lack of control cannot be tolerated, but on the other side, the large range of possible contexts in which these applications will execute still require dynamism, flexibility and still defeats the possibility to define an application by the list of its components. The challenge we face is to find a new way to define applications such that they can fit in a large range of unknown contexts, capable to adapt themselves to multitude of environments and to unknown competing applications, but still with execution strictly controlled and strong properties enforced. The paper describes the Apam platform, its way to describe applications, and the way they are executed. We show how Apam reconciles the two, apparently conflicting, requirements: flexibility and strong control; both at compile and execution time.
@InProceedings{PESOS13p21,
author = {Jacky Estublier and German Vega},
title = {Building Reliable Dynamic Applications for Ubiquitous Computing},
booktitle = {Proc.\ PESOS},
publisher = {IEEE},
pages = {21--28},
doi = {},
year = {2013},
}
PESOS '13: "RESTful Business Process Management ..."
RESTful Business Process Management in the Cloud
Alessio Gambi and Cesare Pautasso
(University of Lugano, Switzerland; TU Vienna, Austria)
As more and more business processes are migrated into cloud-based runtimes, there is a need to manage their state to provide support for quality attributes such as elasticity, scalability and dependability. In this paper we discuss how the REST architectural style provides a sensible choice to manage and publish service compositions under the Platform as a Service paradigm. We define the design principles of RESTful business process management in the cloud and compare several architectural alternatives to support elastic processes which can be monitored and dynamically adapted to workload changes.
@InProceedings{PESOS13p1,
author = {Alessio Gambi and Cesare Pautasso},
title = {RESTful Business Process Management in the Cloud},
booktitle = {Proc.\ PESOS},
publisher = {IEEE},
pages = {1--10},
doi = {},
year = {2013},
}
PESOS '13: "Storm Prediction in a Cloud ..."
Storm Prediction in a Cloud
Ian Davis, Hadi Hemmati, Richard C. Holt, Michael W. Godfrey, Douglas Neuse, and Serge Mankovskii
(University of Waterloo, Canada; CA Technologies, USA)
Predicting future behavior reliably and efficiently is key for systems that manage virtual services; such systems must be able to balance loads within a cloud environment to ensure that service level agreements are met at a reasonable expense. In principle accurate predictions can be achieved by mining a variety of data sources, which describe the historic behavior of the services, the requirements of the programs running on them, and the evolving demands placed on the cloud by end users. Of particular importance is accurate prediction of maximal loads likely to be observed in the short term. However, standard approaches to modeling system behavior, by analyzing the totality of the observed data, tend to predict average rather than exceptional system behavior and ignore important patterns of change over time. In this paper, we study the ability of a simple multivariate linear regression for forecasting of peak CPU utilization (storm) in an industrial cloud environment. We also propose several modifications to the standard linear regression to adjust it for storm prediction.
@InProceedings{PESOS13p37,
author = {Ian Davis and Hadi Hemmati and Richard C. Holt and Michael W. Godfrey and Douglas Neuse and Serge Mankovskii},
title = {Storm Prediction in a Cloud},
booktitle = {Proc.\ PESOS},
publisher = {IEEE},
pages = {37--40},
doi = {},
year = {2013},
}
PESOS '13: "Storm Prediction in a Cloud ..."
Storm Prediction in a Cloud
Ian Davis, Hadi Hemmati, Richard C. Holt, Michael W. Godfrey, Douglas Neuse, and Serge Mankovskii
(University of Waterloo, Canada; CA Technologies, USA)
Predicting future behavior reliably and efficiently is key for systems that manage virtual services; such systems must be able to balance loads within a cloud environment to ensure that service level agreements are met at a reasonable expense. In principle accurate predictions can be achieved by mining a variety of data sources, which describe the historic behavior of the services, the requirements of the programs running on them, and the evolving demands placed on the cloud by end users. Of particular importance is accurate prediction of maximal loads likely to be observed in the short term. However, standard approaches to modeling system behavior, by analyzing the totality of the observed data, tend to predict average rather than exceptional system behavior and ignore important patterns of change over time. In this paper, we study the ability of a simple multivariate linear regression for forecasting of peak CPU utilization (storm) in an industrial cloud environment. We also propose several modifications to the standard linear regression to adjust it for storm prediction.
@InProceedings{PESOS13p37,
author = {Ian Davis and Hadi Hemmati and Richard C. Holt and Michael W. Godfrey and Douglas Neuse and Serge Mankovskii},
title = {Storm Prediction in a Cloud},
booktitle = {Proc.\ PESOS},
publisher = {IEEE},
pages = {37--40},
doi = {},
year = {2013},
}
PESOS '13: "Framework for Evaluating Reusability ..."
Framework for Evaluating Reusability of Component-as-a-Service (CaaS)
Hyun Jung La, Jin Sun Her, and Soo Dong Kim
(Soongsil University, South Korea)
As a form of service, Component-as-a-Service (CaaS) provides a reusable functionality which is subscribed by and integrated into service-based applications. Hence, the reusability of CaaS is a key factor for its value. This paper proposes a comprehensive reusability evaluation framework for CaaS. We derive a set of CaaS reusability attributes by applying a logical and objective process, and define metrics for key attributes with the focuses on theoretical soundness and practical applicability. The proposed reusability evaluation suite is assessed with a case study.
@InProceedings{PESOS13p41,
author = {Hyun Jung La and Jin Sun Her and Soo Dong Kim},
title = {Framework for Evaluating Reusability of Component-as-a-Service (CaaS)},
booktitle = {Proc.\ PESOS},
publisher = {IEEE},
pages = {41--44},
doi = {},
year = {2013},
}
PESOS '13: "Storm Prediction in a Cloud ..."
Storm Prediction in a Cloud
Ian Davis, Hadi Hemmati, Richard C. Holt, Michael W. Godfrey, Douglas Neuse, and Serge Mankovskii
(University of Waterloo, Canada; CA Technologies, USA)
Predicting future behavior reliably and efficiently is key for systems that manage virtual services; such systems must be able to balance loads within a cloud environment to ensure that service level agreements are met at a reasonable expense. In principle accurate predictions can be achieved by mining a variety of data sources, which describe the historic behavior of the services, the requirements of the programs running on them, and the evolving demands placed on the cloud by end users. Of particular importance is accurate prediction of maximal loads likely to be observed in the short term. However, standard approaches to modeling system behavior, by analyzing the totality of the observed data, tend to predict average rather than exceptional system behavior and ignore important patterns of change over time. In this paper, we study the ability of a simple multivariate linear regression for forecasting of peak CPU utilization (storm) in an industrial cloud environment. We also propose several modifications to the standard linear regression to adjust it for storm prediction.
@InProceedings{PESOS13p37,
author = {Ian Davis and Hadi Hemmati and Richard C. Holt and Michael W. Godfrey and Douglas Neuse and Serge Mankovskii},
title = {Storm Prediction in a Cloud},
booktitle = {Proc.\ PESOS},
publisher = {IEEE},
pages = {37--40},
doi = {},
year = {2013},
}
PESOS '13: "Towards QoS Prediction Based ..."
Towards QoS Prediction Based on Composition Structure Analysis and Probabilistic Environment Models
Dragan Ivanović, Peerachai Kaowichakorn, and Manuel Carro
(UPM, Spain; IMDEA Software Institute, Spain)
Complex software systems are usually built by composing numerous components, including external services. The quality of service (QoS) is essential for determining the usability of such systems, and depends both on the structure of the composition and on the QoS of its components. Since the QoS of each component is usually determined with uncertainty and varies from one invocation to another, the composite system also exhibits stochastic QoS behavior. We propose an approach for computing probability distributions of the composite system QoS attributes based on known probability distributions of the component QoS attributes and the composition structure. The approach is experimentally evaluated using a prototype analyzer tool and a real-world service-based example, by comparing the predicted probability distributions for the composition QoS with the actual distribution of QoS values from repeated actual executions.
@InProceedings{PESOS13p11,
author = {Dragan Ivanović and Peerachai Kaowichakorn and Manuel Carro},
title = {Towards QoS Prediction Based on Composition Structure Analysis and Probabilistic Environment Models},
booktitle = {Proc.\ PESOS},
publisher = {IEEE},
pages = {11--20},
doi = {},
year = {2013},
}
PESOS '13: "Towards QoS Prediction Based ..."
Towards QoS Prediction Based on Composition Structure Analysis and Probabilistic Environment Models
Dragan Ivanović, Peerachai Kaowichakorn, and Manuel Carro
(UPM, Spain; IMDEA Software Institute, Spain)
Complex software systems are usually built by composing numerous components, including external services. The quality of service (QoS) is essential for determining the usability of such systems, and depends both on the structure of the composition and on the QoS of its components. Since the QoS of each component is usually determined with uncertainty and varies from one invocation to another, the composite system also exhibits stochastic QoS behavior. We propose an approach for computing probability distributions of the composite system QoS attributes based on known probability distributions of the component QoS attributes and the composition structure. The approach is experimentally evaluated using a prototype analyzer tool and a real-world service-based example, by comparing the predicted probability distributions for the composition QoS with the actual distribution of QoS values from repeated actual executions.
@InProceedings{PESOS13p11,
author = {Dragan Ivanović and Peerachai Kaowichakorn and Manuel Carro},
title = {Towards QoS Prediction Based on Composition Structure Analysis and Probabilistic Environment Models},
booktitle = {Proc.\ PESOS},
publisher = {IEEE},
pages = {11--20},
doi = {},
year = {2013},
}
PESOS '13: "Framework for Evaluating Reusability ..."
Framework for Evaluating Reusability of Component-as-a-Service (CaaS)
Hyun Jung La, Jin Sun Her, and Soo Dong Kim
(Soongsil University, South Korea)
As a form of service, Component-as-a-Service (CaaS) provides a reusable functionality which is subscribed by and integrated into service-based applications. Hence, the reusability of CaaS is a key factor for its value. This paper proposes a comprehensive reusability evaluation framework for CaaS. We derive a set of CaaS reusability attributes by applying a logical and objective process, and define metrics for key attributes with the focuses on theoretical soundness and practical applicability. The proposed reusability evaluation suite is assessed with a case study.
@InProceedings{PESOS13p41,
author = {Hyun Jung La and Jin Sun Her and Soo Dong Kim},
title = {Framework for Evaluating Reusability of Component-as-a-Service (CaaS)},
booktitle = {Proc.\ PESOS},
publisher = {IEEE},
pages = {41--44},
doi = {},
year = {2013},
}
PESOS '13: "Framework for Evaluating Reusability ..."
Framework for Evaluating Reusability of Component-as-a-Service (CaaS)
Hyun Jung La, Jin Sun Her, and Soo Dong Kim
(Soongsil University, South Korea)
As a form of service, Component-as-a-Service (CaaS) provides a reusable functionality which is subscribed by and integrated into service-based applications. Hence, the reusability of CaaS is a key factor for its value. This paper proposes a comprehensive reusability evaluation framework for CaaS. We derive a set of CaaS reusability attributes by applying a logical and objective process, and define metrics for key attributes with the focuses on theoretical soundness and practical applicability. The proposed reusability evaluation suite is assessed with a case study.
@InProceedings{PESOS13p41,
author = {Hyun Jung La and Jin Sun Her and Soo Dong Kim},
title = {Framework for Evaluating Reusability of Component-as-a-Service (CaaS)},
booktitle = {Proc.\ PESOS},
publisher = {IEEE},
pages = {41--44},
doi = {},
year = {2013},
}
PESOS '13: "Dynamic Program Code Distribution ..."
Dynamic Program Code Distribution in Infrastructure-as-a-Service Clouds
Rostyslav Zabolotnyi, Philipp Leitner, and Schahram Dustdar
(TU Vienna, Austria)
Elastically scaling cloud computing applications are becoming more and more prevalent in today's IT landscapes. One problem of building such applications in an Infrastructure-as-a-Service cloud is the runtime distribution of program code, configuration files and other resources. While it is possible to include all required program code in the used IaaS base images, this severely restricts the achievable dynamicity at runtime. In this paper, we present a framework for dynamic program code distribution. Our approach handles code distribution entirely transparently on middleware layer. We base our solution on an existing middleware, CloudScale. The paper discusses the design and implementation of our code distribution approach on top of CloudScale, and numerically evaluates the practicability and performance of the approach based on an illustrative case study.
@InProceedings{PESOS13p29,
author = {Rostyslav Zabolotnyi and Philipp Leitner and Schahram Dustdar},
title = {Dynamic Program Code Distribution in Infrastructure-as-a-Service Clouds},
booktitle = {Proc.\ PESOS},
publisher = {IEEE},
pages = {29--36},
doi = {},
year = {2013},
}
PESOS '13: "The Dark Side of SOA Testing: ..."
The Dark Side of SOA Testing: Towards Testing Contemporary SOAs Based on Criticality Metrics
Philipp Leitner, Stefan Schulte, Schahram Dustdar, Ingo Pill, Marco Schulz, and Franz Wotawa
(TU Vienna, Austria; TU Graz, Austria)
Service-Oriented Architectures (SOAs) have widely been accepted as the standard way of building large-scale, heterogeneous enterprise IT systems. In this paper, we explore the current limitations of testing contemporary SOAs, which are typically assemblies of various components, including services, message buses, business processes, and support components. We argue that, currently, SOA testing is too much concerned with testing single services or business processes, while there is little scientific literature on holistic testing of contemporary SOAs that includes all critical components and their mutual dependencies and interactions. In this paper, we detail the architecture of contemporary SOA, thoroughly assess the current state of research in respect of their testing, and introduce the notion of SOA criticality metrics as indicators for an individual component's criticality for the SOA as a whole. We enumerate an initial metric set for various component types and interactions, as well as discuss how these metrics can be used for testing contemporary SOA.
@InProceedings{PESOS13p45,
author = {Philipp Leitner and Stefan Schulte and Schahram Dustdar and Ingo Pill and Marco Schulz and Franz Wotawa},
title = {The Dark Side of SOA Testing: Towards Testing Contemporary SOAs Based on Criticality Metrics},
booktitle = {Proc.\ PESOS},
publisher = {IEEE},
pages = {45--53},
doi = {},
year = {2013},
}
PESOS '13: "Storm Prediction in a Cloud ..."
Storm Prediction in a Cloud
Ian Davis, Hadi Hemmati, Richard C. Holt, Michael W. Godfrey, Douglas Neuse, and Serge Mankovskii
(University of Waterloo, Canada; CA Technologies, USA)
Predicting future behavior reliably and efficiently is key for systems that manage virtual services; such systems must be able to balance loads within a cloud environment to ensure that service level agreements are met at a reasonable expense. In principle accurate predictions can be achieved by mining a variety of data sources, which describe the historic behavior of the services, the requirements of the programs running on them, and the evolving demands placed on the cloud by end users. Of particular importance is accurate prediction of maximal loads likely to be observed in the short term. However, standard approaches to modeling system behavior, by analyzing the totality of the observed data, tend to predict average rather than exceptional system behavior and ignore important patterns of change over time. In this paper, we study the ability of a simple multivariate linear regression for forecasting of peak CPU utilization (storm) in an industrial cloud environment. We also propose several modifications to the standard linear regression to adjust it for storm prediction.
@InProceedings{PESOS13p37,
author = {Ian Davis and Hadi Hemmati and Richard C. Holt and Michael W. Godfrey and Douglas Neuse and Serge Mankovskii},
title = {Storm Prediction in a Cloud},
booktitle = {Proc.\ PESOS},
publisher = {IEEE},
pages = {37--40},
doi = {},
year = {2013},
}
PESOS '13: "Storm Prediction in a Cloud ..."
Storm Prediction in a Cloud
Ian Davis, Hadi Hemmati, Richard C. Holt, Michael W. Godfrey, Douglas Neuse, and Serge Mankovskii
(University of Waterloo, Canada; CA Technologies, USA)
Predicting future behavior reliably and efficiently is key for systems that manage virtual services; such systems must be able to balance loads within a cloud environment to ensure that service level agreements are met at a reasonable expense. In principle accurate predictions can be achieved by mining a variety of data sources, which describe the historic behavior of the services, the requirements of the programs running on them, and the evolving demands placed on the cloud by end users. Of particular importance is accurate prediction of maximal loads likely to be observed in the short term. However, standard approaches to modeling system behavior, by analyzing the totality of the observed data, tend to predict average rather than exceptional system behavior and ignore important patterns of change over time. In this paper, we study the ability of a simple multivariate linear regression for forecasting of peak CPU utilization (storm) in an industrial cloud environment. We also propose several modifications to the standard linear regression to adjust it for storm prediction.
@InProceedings{PESOS13p37,
author = {Ian Davis and Hadi Hemmati and Richard C. Holt and Michael W. Godfrey and Douglas Neuse and Serge Mankovskii},
title = {Storm Prediction in a Cloud},
booktitle = {Proc.\ PESOS},
publisher = {IEEE},
pages = {37--40},
doi = {},
year = {2013},
}
PESOS '13: "RESTful Business Process Management ..."
RESTful Business Process Management in the Cloud
Alessio Gambi and Cesare Pautasso
(University of Lugano, Switzerland; TU Vienna, Austria)
As more and more business processes are migrated into cloud-based runtimes, there is a need to manage their state to provide support for quality attributes such as elasticity, scalability and dependability. In this paper we discuss how the REST architectural style provides a sensible choice to manage and publish service compositions under the Platform as a Service paradigm. We define the design principles of RESTful business process management in the cloud and compare several architectural alternatives to support elastic processes which can be monitored and dynamically adapted to workload changes.
@InProceedings{PESOS13p1,
author = {Alessio Gambi and Cesare Pautasso},
title = {RESTful Business Process Management in the Cloud},
booktitle = {Proc.\ PESOS},
publisher = {IEEE},
pages = {1--10},
doi = {},
year = {2013},
}
PESOS '13: "The Dark Side of SOA Testing: ..."
The Dark Side of SOA Testing: Towards Testing Contemporary SOAs Based on Criticality Metrics
Philipp Leitner, Stefan Schulte, Schahram Dustdar, Ingo Pill, Marco Schulz, and Franz Wotawa
(TU Vienna, Austria; TU Graz, Austria)
Service-Oriented Architectures (SOAs) have widely been accepted as the standard way of building large-scale, heterogeneous enterprise IT systems. In this paper, we explore the current limitations of testing contemporary SOAs, which are typically assemblies of various components, including services, message buses, business processes, and support components. We argue that, currently, SOA testing is too much concerned with testing single services or business processes, while there is little scientific literature on holistic testing of contemporary SOAs that includes all critical components and their mutual dependencies and interactions. In this paper, we detail the architecture of contemporary SOA, thoroughly assess the current state of research in respect of their testing, and introduce the notion of SOA criticality metrics as indicators for an individual component's criticality for the SOA as a whole. We enumerate an initial metric set for various component types and interactions, as well as discuss how these metrics can be used for testing contemporary SOA.
@InProceedings{PESOS13p45,
author = {Philipp Leitner and Stefan Schulte and Schahram Dustdar and Ingo Pill and Marco Schulz and Franz Wotawa},
title = {The Dark Side of SOA Testing: Towards Testing Contemporary SOAs Based on Criticality Metrics},
booktitle = {Proc.\ PESOS},
publisher = {IEEE},
pages = {45--53},
doi = {},
year = {2013},
}
PESOS '13: "The Dark Side of SOA Testing: ..."
The Dark Side of SOA Testing: Towards Testing Contemporary SOAs Based on Criticality Metrics
Philipp Leitner, Stefan Schulte, Schahram Dustdar, Ingo Pill, Marco Schulz, and Franz Wotawa
(TU Vienna, Austria; TU Graz, Austria)
Service-Oriented Architectures (SOAs) have widely been accepted as the standard way of building large-scale, heterogeneous enterprise IT systems. In this paper, we explore the current limitations of testing contemporary SOAs, which are typically assemblies of various components, including services, message buses, business processes, and support components. We argue that, currently, SOA testing is too much concerned with testing single services or business processes, while there is little scientific literature on holistic testing of contemporary SOAs that includes all critical components and their mutual dependencies and interactions. In this paper, we detail the architecture of contemporary SOA, thoroughly assess the current state of research in respect of their testing, and introduce the notion of SOA criticality metrics as indicators for an individual component's criticality for the SOA as a whole. We enumerate an initial metric set for various component types and interactions, as well as discuss how these metrics can be used for testing contemporary SOA.
@InProceedings{PESOS13p45,
author = {Philipp Leitner and Stefan Schulte and Schahram Dustdar and Ingo Pill and Marco Schulz and Franz Wotawa},
title = {The Dark Side of SOA Testing: Towards Testing Contemporary SOAs Based on Criticality Metrics},
booktitle = {Proc.\ PESOS},
publisher = {IEEE},
pages = {45--53},
doi = {},
year = {2013},
}
PESOS '13: "The Dark Side of SOA Testing: ..."
The Dark Side of SOA Testing: Towards Testing Contemporary SOAs Based on Criticality Metrics
Philipp Leitner, Stefan Schulte, Schahram Dustdar, Ingo Pill, Marco Schulz, and Franz Wotawa
(TU Vienna, Austria; TU Graz, Austria)
Service-Oriented Architectures (SOAs) have widely been accepted as the standard way of building large-scale, heterogeneous enterprise IT systems. In this paper, we explore the current limitations of testing contemporary SOAs, which are typically assemblies of various components, including services, message buses, business processes, and support components. We argue that, currently, SOA testing is too much concerned with testing single services or business processes, while there is little scientific literature on holistic testing of contemporary SOAs that includes all critical components and their mutual dependencies and interactions. In this paper, we detail the architecture of contemporary SOA, thoroughly assess the current state of research in respect of their testing, and introduce the notion of SOA criticality metrics as indicators for an individual component's criticality for the SOA as a whole. We enumerate an initial metric set for various component types and interactions, as well as discuss how these metrics can be used for testing contemporary SOA.
@InProceedings{PESOS13p45,
author = {Philipp Leitner and Stefan Schulte and Schahram Dustdar and Ingo Pill and Marco Schulz and Franz Wotawa},
title = {The Dark Side of SOA Testing: Towards Testing Contemporary SOAs Based on Criticality Metrics},
booktitle = {Proc.\ PESOS},
publisher = {IEEE},
pages = {45--53},
doi = {},
year = {2013},
}
PESOS '13: "Building Reliable Dynamic ..."
Building Reliable Dynamic Applications for Ubiquitous Computing
Jacky Estublier and German Vega
(LIG, France; Grenoble University, France)
Service platforms emphasize dynamism and flexibility, at the cost of very little control over applications execution. Indeed, service platforms like OSGi do not provide an application concept or any structuring concept; they only support a flat space of services and a low-level run-time protocol. This was acceptable because, so far, a single application made of well-known services was running inside a platform. This was convenient because, in ubiquitous and dynamic environments, the available services and their dynamic behavior are not known in advance, eliminating the possibility to define an application by the list of its components. In the near future, service platform will support many shared services from independent providers and many applications managing critical services, like home security applications. Although, in this context, the lack of control cannot be tolerated, but on the other side, the large range of possible contexts in which these applications will execute still require dynamism, flexibility and still defeats the possibility to define an application by the list of its components. The challenge we face is to find a new way to define applications such that they can fit in a large range of unknown contexts, capable to adapt themselves to multitude of environments and to unknown competing applications, but still with execution strictly controlled and strong properties enforced. The paper describes the Apam platform, its way to describe applications, and the way they are executed. We show how Apam reconciles the two, apparently conflicting, requirements: flexibility and strong control; both at compile and execution time.
@InProceedings{PESOS13p21,
author = {Jacky Estublier and German Vega},
title = {Building Reliable Dynamic Applications for Ubiquitous Computing},
booktitle = {Proc.\ PESOS},
publisher = {IEEE},
pages = {21--28},
doi = {},
year = {2013},
}
PESOS '13: "The Dark Side of SOA Testing: ..."
The Dark Side of SOA Testing: Towards Testing Contemporary SOAs Based on Criticality Metrics
Philipp Leitner, Stefan Schulte, Schahram Dustdar, Ingo Pill, Marco Schulz, and Franz Wotawa
(TU Vienna, Austria; TU Graz, Austria)
Service-Oriented Architectures (SOAs) have widely been accepted as the standard way of building large-scale, heterogeneous enterprise IT systems. In this paper, we explore the current limitations of testing contemporary SOAs, which are typically assemblies of various components, including services, message buses, business processes, and support components. We argue that, currently, SOA testing is too much concerned with testing single services or business processes, while there is little scientific literature on holistic testing of contemporary SOAs that includes all critical components and their mutual dependencies and interactions. In this paper, we detail the architecture of contemporary SOA, thoroughly assess the current state of research in respect of their testing, and introduce the notion of SOA criticality metrics as indicators for an individual component's criticality for the SOA as a whole. We enumerate an initial metric set for various component types and interactions, as well as discuss how these metrics can be used for testing contemporary SOA.
@InProceedings{PESOS13p45,
author = {Philipp Leitner and Stefan Schulte and Schahram Dustdar and Ingo Pill and Marco Schulz and Franz Wotawa},
title = {The Dark Side of SOA Testing: Towards Testing Contemporary SOAs Based on Criticality Metrics},
booktitle = {Proc.\ PESOS},
publisher = {IEEE},
pages = {45--53},
doi = {},
year = {2013},
}
PESOS '13: "Dynamic Program Code Distribution ..."
Dynamic Program Code Distribution in Infrastructure-as-a-Service Clouds
Rostyslav Zabolotnyi, Philipp Leitner, and Schahram Dustdar
(TU Vienna, Austria)
Elastically scaling cloud computing applications are becoming more and more prevalent in today's IT landscapes. One problem of building such applications in an Infrastructure-as-a-Service cloud is the runtime distribution of program code, configuration files and other resources. While it is possible to include all required program code in the used IaaS base images, this severely restricts the achievable dynamicity at runtime. In this paper, we present a framework for dynamic program code distribution. Our approach handles code distribution entirely transparently on middleware layer. We base our solution on an existing middleware, CloudScale. The paper discusses the design and implementation of our code distribution approach on top of CloudScale, and numerically evaluates the practicability and performance of the approach based on an illustrative case study.
@InProceedings{PESOS13p29,
author = {Rostyslav Zabolotnyi and Philipp Leitner and Schahram Dustdar},
title = {Dynamic Program Code Distribution in Infrastructure-as-a-Service Clouds},
booktitle = {Proc.\ PESOS},
publisher = {IEEE},
pages = {29--36},
doi = {},
year = {2013},
}