MESOCA '15: "Cloud Compliant Applications: ..."
Cloud Compliant Applications: A Reference Framework to Assess the Maturity of Software Applications with Respect to Cloud
Juncal Alonso, Leire Orue-Echevarria, and Marisa Escalante
(Tecnalia, Spain)
Over the last years several standards and reports have been pub-lished and released (ISO CCRA, TOSCA), where best practices with respect to Cloud based application design, development and deployment are described. Other frameworks such as ITIL or EFQM provide recommendations for identifying, planning, deliv-ering and supporting IT services to the business through adapta-tion of the business models and processes. All this best practices are scattered through different sources and there is not a unique criteria covering all the aspects. This paper proposes a maturity assessment approach support-ed by tools based on standards widely adopted in the industry. It covers best practices in the three dimensions and ranks the pos-sible solutions in terms of the most suitable alternatives for cloud based solutions. The maturity assessment has been also comple-mented with the functionality of capturing user information, and transforming it in useful information in terms of reports and files for the migration process.
@InProceedings{MESOCA15p41,
author = {Juncal Alonso and Leire Orue-Echevarria and Marisa Escalante},
title = {Cloud Compliant Applications: A Reference Framework to Assess the Maturity of Software Applications with Respect to Cloud},
booktitle = {Proc.\ MESOCA},
publisher = {IEEE},
pages = {41--45},
doi = {},
year = {2015},
}
MESOCA '15: "MonSLAR: A Middleware for ..."
MonSLAR: A Middleware for Monitoring SLA for RESTFUL Services in Cloud Computing
Shaymaa Al-Shammari and Adil Al-Yasiri
(University of Salford, UK)
Measuring the quality of cloud computing provision from the client’s point of view is important in order to ensure that the service conforms to the level specified in the service level agreement (SLA). With a view to avoid SLA violation, the main parameters should be determined in the agreement and then used to evaluate the fulfillment of the SLA terms at the client’s side. Current studies in cloud monitoring only handle monitoring the provider resources with little or no consideration to the client’s side. This paper presents MonSLAR, a user-centric middleware for Monitoring SLA for Restful services in SaaS cloud computing environments. MonSLAR uses a distributed architecture that allows SLA parameters and the monitored data to be embedded in the requests and responses of the REST protocol.
@InProceedings{MESOCA15p46,
author = {Shaymaa Al-Shammari and Adil Al-Yasiri},
title = {MonSLAR: A Middleware for Monitoring SLA for RESTFUL Services in Cloud Computing},
booktitle = {Proc.\ MESOCA},
publisher = {IEEE},
pages = {46--50},
doi = {},
year = {2015},
}
MESOCA '15: "MonSLAR: A Middleware for ..."
MonSLAR: A Middleware for Monitoring SLA for RESTFUL Services in Cloud Computing
Shaymaa Al-Shammari and Adil Al-Yasiri
(University of Salford, UK)
Measuring the quality of cloud computing provision from the client’s point of view is important in order to ensure that the service conforms to the level specified in the service level agreement (SLA). With a view to avoid SLA violation, the main parameters should be determined in the agreement and then used to evaluate the fulfillment of the SLA terms at the client’s side. Current studies in cloud monitoring only handle monitoring the provider resources with little or no consideration to the client’s side. This paper presents MonSLAR, a user-centric middleware for Monitoring SLA for Restful services in SaaS cloud computing environments. MonSLAR uses a distributed architecture that allows SLA parameters and the monitored data to be embedded in the requests and responses of the REST protocol.
@InProceedings{MESOCA15p46,
author = {Shaymaa Al-Shammari and Adil Al-Yasiri},
title = {MonSLAR: A Middleware for Monitoring SLA for RESTFUL Services in Cloud Computing},
booktitle = {Proc.\ MESOCA},
publisher = {IEEE},
pages = {46--50},
doi = {},
year = {2015},
}
MESOCA '15: "Challenges and Assessment ..."
Challenges and Assessment in Migrating IT Legacy Applications to the Cloud
Patrizia Scandurra, Giuseppe Psaila, Rafael Capilla, and Raffaela Mirandola
(University of Bergamo, Italy; Rey Juan Carlos University, Spain; Politecnico di Milano, Italy)
The incessant trend where software engineers need to redesign legacy systems adopting a service-centric engineering approach brings new challenges for software architects and developers. Today, engineering and deploying software as a service requires specific Internet protocols, middleware and languages that often complicate the interoperability of software at all levels. Moreover, cloud computing demands stringent quality requirements, such as security, scalability, and interoperability among others, to provide services and data across networks more efficiently. As software engineers must face the problem to redesign and redeploy systems as services, we explore in this paper the challenges found during the migration of an existing system to a cloud solution and based on a set of quality requirements that includes the vendor lock-in factor. We also present a set of as-sessment activities and guidelines to support migration to the Cloud by adopting SOA and Cloud modeling standards and tools.
@InProceedings{MESOCA15p7,
author = {Patrizia Scandurra and Giuseppe Psaila and Rafael Capilla and Raffaela Mirandola},
title = {Challenges and Assessment in Migrating IT Legacy Applications to the Cloud},
booktitle = {Proc.\ MESOCA},
publisher = {IEEE},
pages = {7--14},
doi = {},
year = {2015},
}
MESOCA '15: "Cloud Compliant Applications: ..."
Cloud Compliant Applications: A Reference Framework to Assess the Maturity of Software Applications with Respect to Cloud
Juncal Alonso, Leire Orue-Echevarria, and Marisa Escalante
(Tecnalia, Spain)
Over the last years several standards and reports have been pub-lished and released (ISO CCRA, TOSCA), where best practices with respect to Cloud based application design, development and deployment are described. Other frameworks such as ITIL or EFQM provide recommendations for identifying, planning, deliv-ering and supporting IT services to the business through adapta-tion of the business models and processes. All this best practices are scattered through different sources and there is not a unique criteria covering all the aspects. This paper proposes a maturity assessment approach support-ed by tools based on standards widely adopted in the industry. It covers best practices in the three dimensions and ranks the pos-sible solutions in terms of the most suitable alternatives for cloud based solutions. The maturity assessment has been also comple-mented with the functionality of capturing user information, and transforming it in useful information in terms of reports and files for the migration process.
@InProceedings{MESOCA15p41,
author = {Juncal Alonso and Leire Orue-Echevarria and Marisa Escalante},
title = {Cloud Compliant Applications: A Reference Framework to Assess the Maturity of Software Applications with Respect to Cloud},
booktitle = {Proc.\ MESOCA},
publisher = {IEEE},
pages = {41--45},
doi = {},
year = {2015},
}
MESOCA '15: "Evaluating Cluster Configurations ..."
Evaluating Cluster Configurations for Big Data Processing: An Exploratory Study
Roni Sandel, Mark Shtern, Marios Fokaefs, and Marin Litoiu
(York University, Canada)
As data continues to grow rapidly, NoSQL clusters have been increasingly adopted to address the storage and processing demands of these large amounts of data. In parallel, cloud computing is also increasingly being adopted due to its flexibility, cost efficiency and scalability. However, evaluating and modelling NoSQL clusters present many challenges. In this work, we explore these challenges by performing a series of experiments with various configurations. The intuition is that this process is laborious and expensive and the goal of our experiments is to confirm this intuition and to identify the factors that impact the performance of a Big Data cluster. Our experiments mostly focus on three factors: data compression, data schema and cluster topology. We performed a number of experiments based on these factors and measured and compared the response times of the resulting configurations. Eventually, the outcomes of our study are encapsulated in a performance model that predicts the cluster's response time as a function of the incoming workload and evaluates the cluster's performance less costly and faster. This systematic and effortless evaluation method will facilitate the selection and migration to a better cluster as the performance and budget goals change. We use HBase as the large data processing cluster and we conduct our experiments on traffic data from a large city and on a distributed community cloud infrastructure.
@InProceedings{MESOCA15p23,
author = {Roni Sandel and Mark Shtern and Marios Fokaefs and Marin Litoiu},
title = {Evaluating Cluster Configurations for Big Data Processing: An Exploratory Study},
booktitle = {Proc.\ MESOCA},
publisher = {IEEE},
pages = {23--30},
doi = {},
year = {2015},
}
MESOCA '15: "Architectural Run-Time Models ..."
Architectural Run-Time Models for Operator-in-the-Loop Adaptation of Cloud Applications
Robert Heinrich, Reiner Jung, Eric Schmieders, Andreas Metzger, Wilhelm Hasselbring, Ralf Reussner, and Klaus Pohl
(KIT, Germany; Kiel University, Germany; University of Duisburg-Essen, Germany)
Building software systems by composing third-party cloud services promises many benefits. However, the increased complexity, heterogeneity, and limited observability of cloud services brings fully automatic adaption to its limits. We propose architectural run-time models as a means for combining automatic and operator-in-the-loop adaptations of cloud services.
@InProceedings{MESOCA15p36,
author = {Robert Heinrich and Reiner Jung and Eric Schmieders and Andreas Metzger and Wilhelm Hasselbring and Ralf Reussner and Klaus Pohl},
title = {Architectural Run-Time Models for Operator-in-the-Loop Adaptation of Cloud Applications},
booktitle = {Proc.\ MESOCA},
publisher = {IEEE},
pages = {36--40},
doi = {},
year = {2015},
}
MESOCA '15: "Modeling and Evaluation of ..."
Modeling and Evaluation of Mixed Redundancy Strategy with Instant Switching in Cloud-Based Systems
Pan He, Chun Tan, Xueliang Zhao, and Zhihao Zheng
(Chinese Academy of Sciences, China)
Mixed redundancy strategy is generally used in cloud-based sys-tems, with different node switch mechanism from traditional mixed strategy. However, related researches often concentrates on traditional mixed redundancy strategy in which cold standby components is working only after all active nodes fail. So a model is developed to evaluate the reliability and performance of cloud-based degraded system subjected to mixed active and cold standby redundancy strategy with continual monitoring and detection mechanism. It is assumed that the node switching pro-cess is triggered once some active nodes fail and there are availa-ble standby nodes. A continuous-time Markov chain is built on top of the state transition process and both transient and steady state availability and expected job completion rate are used to evaluate system metrics with or with repair facilities. A numerical method is used to solve the model and sensitivity analysis is con-ducted on different redundancy strategy. Illustrative examples using real-world data were presented to explain the process of calculating the probability of each state and the different kinds of availability and performance. The comparison with traditional mixed redundancy strategy proved that the system behavior was different using different kinds of mixed strategy and the analysis model for traditional strategy was not suitable for strategies in cloud-bases system.
@InProceedings{MESOCA15p15,
author = {Pan He and Chun Tan and Xueliang Zhao and Zhihao Zheng},
title = {Modeling and Evaluation of Mixed Redundancy Strategy with Instant Switching in Cloud-Based Systems},
booktitle = {Proc.\ MESOCA},
publisher = {IEEE},
pages = {15--22},
doi = {},
year = {2015},
}
MESOCA '15: "Architectural Run-Time Models ..."
Architectural Run-Time Models for Operator-in-the-Loop Adaptation of Cloud Applications
Robert Heinrich, Reiner Jung, Eric Schmieders, Andreas Metzger, Wilhelm Hasselbring, Ralf Reussner, and Klaus Pohl
(KIT, Germany; Kiel University, Germany; University of Duisburg-Essen, Germany)
Building software systems by composing third-party cloud services promises many benefits. However, the increased complexity, heterogeneity, and limited observability of cloud services brings fully automatic adaption to its limits. We propose architectural run-time models as a means for combining automatic and operator-in-the-loop adaptations of cloud services.
@InProceedings{MESOCA15p36,
author = {Robert Heinrich and Reiner Jung and Eric Schmieders and Andreas Metzger and Wilhelm Hasselbring and Ralf Reussner and Klaus Pohl},
title = {Architectural Run-Time Models for Operator-in-the-Loop Adaptation of Cloud Applications},
booktitle = {Proc.\ MESOCA},
publisher = {IEEE},
pages = {36--40},
doi = {},
year = {2015},
}
MESOCA '15: "Sustainability Forecast for ..."
Sustainability Forecast for Cloud Migration
Alifah Aida Lope Abdul Rahman and Shareeful Islam
(National Audit Department, Malaysia; University of East London, UK)
In this paper, a sustainability driven approach is proposed to measure the viability of cloud migration. The decision on cloud migration is based on sustainability dimensions, i.e., economic, environmental, social and technology, and risks associated with in these dimensions. We use Analytic Hierarchy Process and fuzzy scale to prioritize the sustainability dimensions based on a migration context to calculate Total Sustainability Index (TSI). TSI is then used to determine the viability of cloud migration according to three different scales, i.e., convincing, moderate, and ineffective. Finally, we used a practical migration use case from Ministry of Health (MoH), Malaysia to demonstrate the applicability of our work. The results from the studied context concluded that economic and business continuity are the key influential concerns for a sustainable cloud migration.
@InProceedings{MESOCA15p31,
author = {Alifah Aida Lope Abdul Rahman and Shareeful Islam},
title = {Sustainability Forecast for Cloud Migration},
booktitle = {Proc.\ MESOCA},
publisher = {IEEE},
pages = {31--35},
doi = {},
year = {2015},
}
MESOCA '15: "Service-Oriented Toolchains ..."
Service-Oriented Toolchains for Software Evolution
Jan Jelschen
(University of Oldenburg, Germany)
Software evolution projects need to be supported by integrated toolchains, yet can suffer from inadequate tool interoperability. Practitioners are forced to deal with technical integration issues, instead of focusing on their projects' actual objectives. Lacking integration support, the resulting toolchains are rigid and inflexible, impeding project progress. This paper presents SENSEI, a service-oriented support framework for toolchain-building, that clearly separates software evolution needs from implementing tools and interoperability issues. It aims to improve interoperability using component-based principles, and provides model-driven code generation to partly automate the integration process. The approach has been prototypically implemented, and was applied in the context of the Q-MIG project, to build parts of an integrated software migration and quality assessment toolchain.
@InProceedings{MESOCA15p51,
author = {Jan Jelschen},
title = {Service-Oriented Toolchains for Software Evolution},
booktitle = {Proc.\ MESOCA},
publisher = {IEEE},
pages = {51--58},
doi = {},
year = {2015},
}
MESOCA '15: "Architectural Run-Time Models ..."
Architectural Run-Time Models for Operator-in-the-Loop Adaptation of Cloud Applications
Robert Heinrich, Reiner Jung, Eric Schmieders, Andreas Metzger, Wilhelm Hasselbring, Ralf Reussner, and Klaus Pohl
(KIT, Germany; Kiel University, Germany; University of Duisburg-Essen, Germany)
Building software systems by composing third-party cloud services promises many benefits. However, the increased complexity, heterogeneity, and limited observability of cloud services brings fully automatic adaption to its limits. We propose architectural run-time models as a means for combining automatic and operator-in-the-loop adaptations of cloud services.
@InProceedings{MESOCA15p36,
author = {Robert Heinrich and Reiner Jung and Eric Schmieders and Andreas Metzger and Wilhelm Hasselbring and Ralf Reussner and Klaus Pohl},
title = {Architectural Run-Time Models for Operator-in-the-Loop Adaptation of Cloud Applications},
booktitle = {Proc.\ MESOCA},
publisher = {IEEE},
pages = {36--40},
doi = {},
year = {2015},
}
MESOCA '15: "Evaluating Cluster Configurations ..."
Evaluating Cluster Configurations for Big Data Processing: An Exploratory Study
Roni Sandel, Mark Shtern, Marios Fokaefs, and Marin Litoiu
(York University, Canada)
As data continues to grow rapidly, NoSQL clusters have been increasingly adopted to address the storage and processing demands of these large amounts of data. In parallel, cloud computing is also increasingly being adopted due to its flexibility, cost efficiency and scalability. However, evaluating and modelling NoSQL clusters present many challenges. In this work, we explore these challenges by performing a series of experiments with various configurations. The intuition is that this process is laborious and expensive and the goal of our experiments is to confirm this intuition and to identify the factors that impact the performance of a Big Data cluster. Our experiments mostly focus on three factors: data compression, data schema and cluster topology. We performed a number of experiments based on these factors and measured and compared the response times of the resulting configurations. Eventually, the outcomes of our study are encapsulated in a performance model that predicts the cluster's response time as a function of the incoming workload and evaluates the cluster's performance less costly and faster. This systematic and effortless evaluation method will facilitate the selection and migration to a better cluster as the performance and budget goals change. We use HBase as the large data processing cluster and we conduct our experiments on traffic data from a large city and on a distributed community cloud infrastructure.
@InProceedings{MESOCA15p23,
author = {Roni Sandel and Mark Shtern and Marios Fokaefs and Marin Litoiu},
title = {Evaluating Cluster Configurations for Big Data Processing: An Exploratory Study},
booktitle = {Proc.\ MESOCA},
publisher = {IEEE},
pages = {23--30},
doi = {},
year = {2015},
}
MESOCA '15: "Architectural Run-Time Models ..."
Architectural Run-Time Models for Operator-in-the-Loop Adaptation of Cloud Applications
Robert Heinrich, Reiner Jung, Eric Schmieders, Andreas Metzger, Wilhelm Hasselbring, Ralf Reussner, and Klaus Pohl
(KIT, Germany; Kiel University, Germany; University of Duisburg-Essen, Germany)
Building software systems by composing third-party cloud services promises many benefits. However, the increased complexity, heterogeneity, and limited observability of cloud services brings fully automatic adaption to its limits. We propose architectural run-time models as a means for combining automatic and operator-in-the-loop adaptations of cloud services.
@InProceedings{MESOCA15p36,
author = {Robert Heinrich and Reiner Jung and Eric Schmieders and Andreas Metzger and Wilhelm Hasselbring and Ralf Reussner and Klaus Pohl},
title = {Architectural Run-Time Models for Operator-in-the-Loop Adaptation of Cloud Applications},
booktitle = {Proc.\ MESOCA},
publisher = {IEEE},
pages = {36--40},
doi = {},
year = {2015},
}
MESOCA '15: "Challenges and Assessment ..."
Challenges and Assessment in Migrating IT Legacy Applications to the Cloud
Patrizia Scandurra, Giuseppe Psaila, Rafael Capilla, and Raffaela Mirandola
(University of Bergamo, Italy; Rey Juan Carlos University, Spain; Politecnico di Milano, Italy)
The incessant trend where software engineers need to redesign legacy systems adopting a service-centric engineering approach brings new challenges for software architects and developers. Today, engineering and deploying software as a service requires specific Internet protocols, middleware and languages that often complicate the interoperability of software at all levels. Moreover, cloud computing demands stringent quality requirements, such as security, scalability, and interoperability among others, to provide services and data across networks more efficiently. As software engineers must face the problem to redesign and redeploy systems as services, we explore in this paper the challenges found during the migration of an existing system to a cloud solution and based on a set of quality requirements that includes the vendor lock-in factor. We also present a set of as-sessment activities and guidelines to support migration to the Cloud by adopting SOA and Cloud modeling standards and tools.
@InProceedings{MESOCA15p7,
author = {Patrizia Scandurra and Giuseppe Psaila and Rafael Capilla and Raffaela Mirandola},
title = {Challenges and Assessment in Migrating IT Legacy Applications to the Cloud},
booktitle = {Proc.\ MESOCA},
publisher = {IEEE},
pages = {7--14},
doi = {},
year = {2015},
}
MESOCA '15: "Cloud Compliant Applications: ..."
Cloud Compliant Applications: A Reference Framework to Assess the Maturity of Software Applications with Respect to Cloud
Juncal Alonso, Leire Orue-Echevarria, and Marisa Escalante
(Tecnalia, Spain)
Over the last years several standards and reports have been pub-lished and released (ISO CCRA, TOSCA), where best practices with respect to Cloud based application design, development and deployment are described. Other frameworks such as ITIL or EFQM provide recommendations for identifying, planning, deliv-ering and supporting IT services to the business through adapta-tion of the business models and processes. All this best practices are scattered through different sources and there is not a unique criteria covering all the aspects. This paper proposes a maturity assessment approach support-ed by tools based on standards widely adopted in the industry. It covers best practices in the three dimensions and ranks the pos-sible solutions in terms of the most suitable alternatives for cloud based solutions. The maturity assessment has been also comple-mented with the functionality of capturing user information, and transforming it in useful information in terms of reports and files for the migration process.
@InProceedings{MESOCA15p41,
author = {Juncal Alonso and Leire Orue-Echevarria and Marisa Escalante},
title = {Cloud Compliant Applications: A Reference Framework to Assess the Maturity of Software Applications with Respect to Cloud},
booktitle = {Proc.\ MESOCA},
publisher = {IEEE},
pages = {41--45},
doi = {},
year = {2015},
}
MESOCA '15: "Architectural Run-Time Models ..."
Architectural Run-Time Models for Operator-in-the-Loop Adaptation of Cloud Applications
Robert Heinrich, Reiner Jung, Eric Schmieders, Andreas Metzger, Wilhelm Hasselbring, Ralf Reussner, and Klaus Pohl
(KIT, Germany; Kiel University, Germany; University of Duisburg-Essen, Germany)
Building software systems by composing third-party cloud services promises many benefits. However, the increased complexity, heterogeneity, and limited observability of cloud services brings fully automatic adaption to its limits. We propose architectural run-time models as a means for combining automatic and operator-in-the-loop adaptations of cloud services.
@InProceedings{MESOCA15p36,
author = {Robert Heinrich and Reiner Jung and Eric Schmieders and Andreas Metzger and Wilhelm Hasselbring and Ralf Reussner and Klaus Pohl},
title = {Architectural Run-Time Models for Operator-in-the-Loop Adaptation of Cloud Applications},
booktitle = {Proc.\ MESOCA},
publisher = {IEEE},
pages = {36--40},
doi = {},
year = {2015},
}
MESOCA '15: "Challenges and Assessment ..."
Challenges and Assessment in Migrating IT Legacy Applications to the Cloud
Patrizia Scandurra, Giuseppe Psaila, Rafael Capilla, and Raffaela Mirandola
(University of Bergamo, Italy; Rey Juan Carlos University, Spain; Politecnico di Milano, Italy)
The incessant trend where software engineers need to redesign legacy systems adopting a service-centric engineering approach brings new challenges for software architects and developers. Today, engineering and deploying software as a service requires specific Internet protocols, middleware and languages that often complicate the interoperability of software at all levels. Moreover, cloud computing demands stringent quality requirements, such as security, scalability, and interoperability among others, to provide services and data across networks more efficiently. As software engineers must face the problem to redesign and redeploy systems as services, we explore in this paper the challenges found during the migration of an existing system to a cloud solution and based on a set of quality requirements that includes the vendor lock-in factor. We also present a set of as-sessment activities and guidelines to support migration to the Cloud by adopting SOA and Cloud modeling standards and tools.
@InProceedings{MESOCA15p7,
author = {Patrizia Scandurra and Giuseppe Psaila and Rafael Capilla and Raffaela Mirandola},
title = {Challenges and Assessment in Migrating IT Legacy Applications to the Cloud},
booktitle = {Proc.\ MESOCA},
publisher = {IEEE},
pages = {7--14},
doi = {},
year = {2015},
}
MESOCA '15: "Sustainability Forecast for ..."
Sustainability Forecast for Cloud Migration
Alifah Aida Lope Abdul Rahman and Shareeful Islam
(National Audit Department, Malaysia; University of East London, UK)
In this paper, a sustainability driven approach is proposed to measure the viability of cloud migration. The decision on cloud migration is based on sustainability dimensions, i.e., economic, environmental, social and technology, and risks associated with in these dimensions. We use Analytic Hierarchy Process and fuzzy scale to prioritize the sustainability dimensions based on a migration context to calculate Total Sustainability Index (TSI). TSI is then used to determine the viability of cloud migration according to three different scales, i.e., convincing, moderate, and ineffective. Finally, we used a practical migration use case from Ministry of Health (MoH), Malaysia to demonstrate the applicability of our work. The results from the studied context concluded that economic and business continuity are the key influential concerns for a sustainable cloud migration.
@InProceedings{MESOCA15p31,
author = {Alifah Aida Lope Abdul Rahman and Shareeful Islam},
title = {Sustainability Forecast for Cloud Migration},
booktitle = {Proc.\ MESOCA},
publisher = {IEEE},
pages = {31--35},
doi = {},
year = {2015},
}
MESOCA '15: "Architectural Run-Time Models ..."
Architectural Run-Time Models for Operator-in-the-Loop Adaptation of Cloud Applications
Robert Heinrich, Reiner Jung, Eric Schmieders, Andreas Metzger, Wilhelm Hasselbring, Ralf Reussner, and Klaus Pohl
(KIT, Germany; Kiel University, Germany; University of Duisburg-Essen, Germany)
Building software systems by composing third-party cloud services promises many benefits. However, the increased complexity, heterogeneity, and limited observability of cloud services brings fully automatic adaption to its limits. We propose architectural run-time models as a means for combining automatic and operator-in-the-loop adaptations of cloud services.
@InProceedings{MESOCA15p36,
author = {Robert Heinrich and Reiner Jung and Eric Schmieders and Andreas Metzger and Wilhelm Hasselbring and Ralf Reussner and Klaus Pohl},
title = {Architectural Run-Time Models for Operator-in-the-Loop Adaptation of Cloud Applications},
booktitle = {Proc.\ MESOCA},
publisher = {IEEE},
pages = {36--40},
doi = {},
year = {2015},
}
MESOCA '15: "Evaluating Cluster Configurations ..."
Evaluating Cluster Configurations for Big Data Processing: An Exploratory Study
Roni Sandel, Mark Shtern, Marios Fokaefs, and Marin Litoiu
(York University, Canada)
As data continues to grow rapidly, NoSQL clusters have been increasingly adopted to address the storage and processing demands of these large amounts of data. In parallel, cloud computing is also increasingly being adopted due to its flexibility, cost efficiency and scalability. However, evaluating and modelling NoSQL clusters present many challenges. In this work, we explore these challenges by performing a series of experiments with various configurations. The intuition is that this process is laborious and expensive and the goal of our experiments is to confirm this intuition and to identify the factors that impact the performance of a Big Data cluster. Our experiments mostly focus on three factors: data compression, data schema and cluster topology. We performed a number of experiments based on these factors and measured and compared the response times of the resulting configurations. Eventually, the outcomes of our study are encapsulated in a performance model that predicts the cluster's response time as a function of the incoming workload and evaluates the cluster's performance less costly and faster. This systematic and effortless evaluation method will facilitate the selection and migration to a better cluster as the performance and budget goals change. We use HBase as the large data processing cluster and we conduct our experiments on traffic data from a large city and on a distributed community cloud infrastructure.
@InProceedings{MESOCA15p23,
author = {Roni Sandel and Mark Shtern and Marios Fokaefs and Marin Litoiu},
title = {Evaluating Cluster Configurations for Big Data Processing: An Exploratory Study},
booktitle = {Proc.\ MESOCA},
publisher = {IEEE},
pages = {23--30},
doi = {},
year = {2015},
}
MESOCA '15: "Challenges and Assessment ..."
Challenges and Assessment in Migrating IT Legacy Applications to the Cloud
Patrizia Scandurra, Giuseppe Psaila, Rafael Capilla, and Raffaela Mirandola
(University of Bergamo, Italy; Rey Juan Carlos University, Spain; Politecnico di Milano, Italy)
The incessant trend where software engineers need to redesign legacy systems adopting a service-centric engineering approach brings new challenges for software architects and developers. Today, engineering and deploying software as a service requires specific Internet protocols, middleware and languages that often complicate the interoperability of software at all levels. Moreover, cloud computing demands stringent quality requirements, such as security, scalability, and interoperability among others, to provide services and data across networks more efficiently. As software engineers must face the problem to redesign and redeploy systems as services, we explore in this paper the challenges found during the migration of an existing system to a cloud solution and based on a set of quality requirements that includes the vendor lock-in factor. We also present a set of as-sessment activities and guidelines to support migration to the Cloud by adopting SOA and Cloud modeling standards and tools.
@InProceedings{MESOCA15p7,
author = {Patrizia Scandurra and Giuseppe Psaila and Rafael Capilla and Raffaela Mirandola},
title = {Challenges and Assessment in Migrating IT Legacy Applications to the Cloud},
booktitle = {Proc.\ MESOCA},
publisher = {IEEE},
pages = {7--14},
doi = {},
year = {2015},
}
MESOCA '15: "Architectural Run-Time Models ..."
Architectural Run-Time Models for Operator-in-the-Loop Adaptation of Cloud Applications
Robert Heinrich, Reiner Jung, Eric Schmieders, Andreas Metzger, Wilhelm Hasselbring, Ralf Reussner, and Klaus Pohl
(KIT, Germany; Kiel University, Germany; University of Duisburg-Essen, Germany)
Building software systems by composing third-party cloud services promises many benefits. However, the increased complexity, heterogeneity, and limited observability of cloud services brings fully automatic adaption to its limits. We propose architectural run-time models as a means for combining automatic and operator-in-the-loop adaptations of cloud services.
@InProceedings{MESOCA15p36,
author = {Robert Heinrich and Reiner Jung and Eric Schmieders and Andreas Metzger and Wilhelm Hasselbring and Ralf Reussner and Klaus Pohl},
title = {Architectural Run-Time Models for Operator-in-the-Loop Adaptation of Cloud Applications},
booktitle = {Proc.\ MESOCA},
publisher = {IEEE},
pages = {36--40},
doi = {},
year = {2015},
}
MESOCA '15: "Evaluating Cluster Configurations ..."
Evaluating Cluster Configurations for Big Data Processing: An Exploratory Study
Roni Sandel, Mark Shtern, Marios Fokaefs, and Marin Litoiu
(York University, Canada)
As data continues to grow rapidly, NoSQL clusters have been increasingly adopted to address the storage and processing demands of these large amounts of data. In parallel, cloud computing is also increasingly being adopted due to its flexibility, cost efficiency and scalability. However, evaluating and modelling NoSQL clusters present many challenges. In this work, we explore these challenges by performing a series of experiments with various configurations. The intuition is that this process is laborious and expensive and the goal of our experiments is to confirm this intuition and to identify the factors that impact the performance of a Big Data cluster. Our experiments mostly focus on three factors: data compression, data schema and cluster topology. We performed a number of experiments based on these factors and measured and compared the response times of the resulting configurations. Eventually, the outcomes of our study are encapsulated in a performance model that predicts the cluster's response time as a function of the incoming workload and evaluates the cluster's performance less costly and faster. This systematic and effortless evaluation method will facilitate the selection and migration to a better cluster as the performance and budget goals change. We use HBase as the large data processing cluster and we conduct our experiments on traffic data from a large city and on a distributed community cloud infrastructure.
@InProceedings{MESOCA15p23,
author = {Roni Sandel and Mark Shtern and Marios Fokaefs and Marin Litoiu},
title = {Evaluating Cluster Configurations for Big Data Processing: An Exploratory Study},
booktitle = {Proc.\ MESOCA},
publisher = {IEEE},
pages = {23--30},
doi = {},
year = {2015},
}
MESOCA '15: "Migrating from Legacy to SoA ..."
Migrating from Legacy to SoA (Invited Talk)
Harry M. Sneed
(SoRing, Hungary; TU Dresden, Germany)
This presentation discusses a strategy for migrating to a service-oriented architecture. The starting point is legacy code in a procedural or object-oriented language. The result is a set of web services that can be accessed in a private or public cloud. The technique used is to cut out selected portions of code and to wrap them behind a service interface. The code itself can be left in the original language. The service interface is in WSDL. The speaker describes how to go about selecting code for reuse and how to extract that code from its current environment. Case studies are given for the languages COBOL and Java. The presentation then goes on to describe how to test the services using a web service testing tool which generates artificial requests from the service interface definition and validates the responses against the assertions provided by the tester.
@InProceedings{MESOCA15p1,
author = {Harry M. Sneed},
title = {Migrating from Legacy to SoA (Invited Talk)},
booktitle = {Proc.\ MESOCA},
publisher = {IEEE},
pages = {1--6},
doi = {},
year = {2015},
}
MESOCA '15: "Measuring Test Coverage of ..."
Measuring Test Coverage of SoA Services
Harry M. Sneed and Chris Verhoef
(SoRing, Hungary; TU Dresden, Germany; VU University Amsterdam, Netherlands)
One of the challenges of testing in a SoA environment is that testers do not have access to the source code of the services they are testing. Therefore they are not able to measure test coverage at the code level, as is done in conventional white-box testing. They are compelled to measure test coverage in other ways which satisfy the constraints of black-box testing. We propose some alternate means of measuring test coverage by focusing on the structure and content of the service interface without regarding the code. The result is a new way of measuring test coverage which can apply to testing in a SoA environment.
@InProceedings{MESOCA15p59,
author = {Harry M. Sneed and Chris Verhoef},
title = {Measuring Test Coverage of SoA Services},
booktitle = {Proc.\ MESOCA},
publisher = {IEEE},
pages = {59--66},
doi = {},
year = {2015},
}
MESOCA '15: "Modeling and Evaluation of ..."
Modeling and Evaluation of Mixed Redundancy Strategy with Instant Switching in Cloud-Based Systems
Pan He, Chun Tan, Xueliang Zhao, and Zhihao Zheng
(Chinese Academy of Sciences, China)
Mixed redundancy strategy is generally used in cloud-based sys-tems, with different node switch mechanism from traditional mixed strategy. However, related researches often concentrates on traditional mixed redundancy strategy in which cold standby components is working only after all active nodes fail. So a model is developed to evaluate the reliability and performance of cloud-based degraded system subjected to mixed active and cold standby redundancy strategy with continual monitoring and detection mechanism. It is assumed that the node switching pro-cess is triggered once some active nodes fail and there are availa-ble standby nodes. A continuous-time Markov chain is built on top of the state transition process and both transient and steady state availability and expected job completion rate are used to evaluate system metrics with or with repair facilities. A numerical method is used to solve the model and sensitivity analysis is con-ducted on different redundancy strategy. Illustrative examples using real-world data were presented to explain the process of calculating the probability of each state and the different kinds of availability and performance. The comparison with traditional mixed redundancy strategy proved that the system behavior was different using different kinds of mixed strategy and the analysis model for traditional strategy was not suitable for strategies in cloud-bases system.
@InProceedings{MESOCA15p15,
author = {Pan He and Chun Tan and Xueliang Zhao and Zhihao Zheng},
title = {Modeling and Evaluation of Mixed Redundancy Strategy with Instant Switching in Cloud-Based Systems},
booktitle = {Proc.\ MESOCA},
publisher = {IEEE},
pages = {15--22},
doi = {},
year = {2015},
}
MESOCA '15: "Measuring Test Coverage of ..."
Measuring Test Coverage of SoA Services
Harry M. Sneed and Chris Verhoef
(SoRing, Hungary; TU Dresden, Germany; VU University Amsterdam, Netherlands)
One of the challenges of testing in a SoA environment is that testers do not have access to the source code of the services they are testing. Therefore they are not able to measure test coverage at the code level, as is done in conventional white-box testing. They are compelled to measure test coverage in other ways which satisfy the constraints of black-box testing. We propose some alternate means of measuring test coverage by focusing on the structure and content of the service interface without regarding the code. The result is a new way of measuring test coverage which can apply to testing in a SoA environment.
@InProceedings{MESOCA15p59,
author = {Harry M. Sneed and Chris Verhoef},
title = {Measuring Test Coverage of SoA Services},
booktitle = {Proc.\ MESOCA},
publisher = {IEEE},
pages = {59--66},
doi = {},
year = {2015},
}
MESOCA '15: "Modeling and Evaluation of ..."
Modeling and Evaluation of Mixed Redundancy Strategy with Instant Switching in Cloud-Based Systems
Pan He, Chun Tan, Xueliang Zhao, and Zhihao Zheng
(Chinese Academy of Sciences, China)
Mixed redundancy strategy is generally used in cloud-based sys-tems, with different node switch mechanism from traditional mixed strategy. However, related researches often concentrates on traditional mixed redundancy strategy in which cold standby components is working only after all active nodes fail. So a model is developed to evaluate the reliability and performance of cloud-based degraded system subjected to mixed active and cold standby redundancy strategy with continual monitoring and detection mechanism. It is assumed that the node switching pro-cess is triggered once some active nodes fail and there are availa-ble standby nodes. A continuous-time Markov chain is built on top of the state transition process and both transient and steady state availability and expected job completion rate are used to evaluate system metrics with or with repair facilities. A numerical method is used to solve the model and sensitivity analysis is con-ducted on different redundancy strategy. Illustrative examples using real-world data were presented to explain the process of calculating the probability of each state and the different kinds of availability and performance. The comparison with traditional mixed redundancy strategy proved that the system behavior was different using different kinds of mixed strategy and the analysis model for traditional strategy was not suitable for strategies in cloud-bases system.
@InProceedings{MESOCA15p15,
author = {Pan He and Chun Tan and Xueliang Zhao and Zhihao Zheng},
title = {Modeling and Evaluation of Mixed Redundancy Strategy with Instant Switching in Cloud-Based Systems},
booktitle = {Proc.\ MESOCA},
publisher = {IEEE},
pages = {15--22},
doi = {},
year = {2015},
}
MESOCA '15: "Modeling and Evaluation of ..."
Modeling and Evaluation of Mixed Redundancy Strategy with Instant Switching in Cloud-Based Systems
Pan He, Chun Tan, Xueliang Zhao, and Zhihao Zheng
(Chinese Academy of Sciences, China)
Mixed redundancy strategy is generally used in cloud-based sys-tems, with different node switch mechanism from traditional mixed strategy. However, related researches often concentrates on traditional mixed redundancy strategy in which cold standby components is working only after all active nodes fail. So a model is developed to evaluate the reliability and performance of cloud-based degraded system subjected to mixed active and cold standby redundancy strategy with continual monitoring and detection mechanism. It is assumed that the node switching pro-cess is triggered once some active nodes fail and there are availa-ble standby nodes. A continuous-time Markov chain is built on top of the state transition process and both transient and steady state availability and expected job completion rate are used to evaluate system metrics with or with repair facilities. A numerical method is used to solve the model and sensitivity analysis is con-ducted on different redundancy strategy. Illustrative examples using real-world data were presented to explain the process of calculating the probability of each state and the different kinds of availability and performance. The comparison with traditional mixed redundancy strategy proved that the system behavior was different using different kinds of mixed strategy and the analysis model for traditional strategy was not suitable for strategies in cloud-bases system.
@InProceedings{MESOCA15p15,
author = {Pan He and Chun Tan and Xueliang Zhao and Zhihao Zheng},
title = {Modeling and Evaluation of Mixed Redundancy Strategy with Instant Switching in Cloud-Based Systems},
booktitle = {Proc.\ MESOCA},
publisher = {IEEE},
pages = {15--22},
doi = {},
year = {2015},
}