�ݺ�ߣshows by User: moldovanus

�ݺ�ߣshows by User: moldovanus / http://www.slideshare.net/images/logo.gif �ݺ�ߣshows by User: moldovanus / Wed, 13 Apr 2016 12:38:10 GMT �ݺ�ߣShare feed for �ݺ�ߣshows by User: moldovanus Cost-aware scalability of applications in public clouds /slideshow/costaware-scalability-of-applications-in-public-clouds/60863481 danielmoldovancostannotated-160413123810
Presentation given in International Conference on Cloud Engineering (IC2E), IEEE, Berlin, Germany, 4-8 April, 2016. Paper accessible on my website http://www.infosys.tuwien.ac.at/staff/dmoldovan/ Scalable applications deployed in public clouds can be built from a combination of custom software components and public cloud services. To meet performance and/or cost requirements, such applications can scale-out/in their components during run-time. When higher performance is required, new component instances can be deployed on newly allocated cloud services (e.g., virtual machines). When the instances are no longer needed, their services can be deallocated to decrease cost. However, public cloud services are usually billed over predefined time and/or usage intervals, e.g., per hour, per GB of I/O. Thus, it might not be cost efficient to scale-in public cloud applications at any moment in time, without considering their billing cycles. In this work we aid developers of scalable applications for public clouds to monitor their costs, and develop cost-aware scalability controllers. We introduce a model for capturing the pricing schemes of cloud services. Based on the model we determine and evaluate the application's costs depending on its used cloud services and their billing cycles. We further evaluate cost efficiency of cloud applications, analyzing which application component is cost efficient to deallocate and when. We integrate our approach in a platform for cost-aware scalability of applications running in public clouds. We evaluate our approach on a scalable platform for IoT, deployed in Flexiant, one of the leading European public cloud providers. We show that cost-aware scalability can achieve higher application stability and performance, while reducing its operation costs.]]>
Presentation given in International Conference on Cloud Engineering (IC2E), IEEE, Berlin, Germany, 4-8 April, 2016. Paper accessible on my website http://www.infosys.tuwien.ac.at/staff/dmoldovan/ Scalable applications deployed in public clouds can be built from a combination of custom software components and public cloud services. To meet performance and/or cost requirements, such applications can scale-out/in their components during run-time. When higher performance is required, new component instances can be deployed on newly allocated cloud services (e.g., virtual machines). When the instances are no longer needed, their services can be deallocated to decrease cost. However, public cloud services are usually billed over predefined time and/or usage intervals, e.g., per hour, per GB of I/O. Thus, it might not be cost efficient to scale-in public cloud applications at any moment in time, without considering their billing cycles. In this work we aid developers of scalable applications for public clouds to monitor their costs, and develop cost-aware scalability controllers. We introduce a model for capturing the pricing schemes of cloud services. Based on the model we determine and evaluate the application's costs depending on its used cloud services and their billing cycles. We further evaluate cost efficiency of cloud applications, analyzing which application component is cost efficient to deallocate and when. We integrate our approach in a platform for cost-aware scalability of applications running in public clouds. We evaluate our approach on a scalable platform for IoT, deployed in Flexiant, one of the leading European public cloud providers. We show that cost-aware scalability can achieve higher application stability and performance, while reducing its operation costs.]]> Wed, 13 Apr 2016 12:38:10 GMT /slideshow/costaware-scalability-of-applications-in-public-clouds/60863481 moldovanus@slideshare.net(moldovanus) Cost-aware scalability of applications in public clouds moldovanus Presentation given in International Conference on Cloud Engineering (IC2E), IEEE, Berlin, Germany, 4-8 April, 2016. Paper accessible on my website http://www.infosys.tuwien.ac.at/staff/dmoldovan/ Scalable applications deployed in public clouds can be built from a combination of custom software components and public cloud services. To meet performance and/or cost requirements, such applications can scale-out/in their components during run-time. When higher performance is required, new component instances can be deployed on newly allocated cloud services (e.g., virtual machines). When the instances are no longer needed, their services can be deallocated to decrease cost. However, public cloud services are usually billed over predefined time and/or usage intervals, e.g., per hour, per GB of I/O. Thus, it might not be cost efficient to scale-in public cloud applications at any moment in time, without considering their billing cycles. In this work we aid developers of scalable applications for public clouds to monitor their costs, and develop cost-aware scalability controllers. We introduce a model for capturing the pricing schemes of cloud services. Based on the model we determine and evaluate the application's costs depending on its used cloud services and their billing cycles. We further evaluate cost efficiency of cloud applications, analyzing which application component is cost efficient to deallocate and when. We integrate our approach in a platform for cost-aware scalability of applications running in public clouds. We evaluate our approach on a scalable platform for IoT, deployed in Flexiant, one of the leading European public cloud providers. We show that cost-aware scalability can achieve higher application stability and performance, while reducing its operation costs. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/danielmoldovancostannotated-160413123810-thumbnail.jpg?width=120&height=120&fit=bounds" /> Presentation given in International Conference on Cloud Engineering (IC2E), IEEE, Berlin, Germany, 4-8 April, 2016. Paper accessible on my website http://www.infosys.tuwien.ac.at/staff/dmoldovan/ Scalable applications deployed in public clouds can be built from a combination of custom software components and public cloud services. To meet performance and/or cost requirements, such applications can scale-out/in their components during run-time. When higher performance is required, new component instances can be deployed on newly allocated cloud services (e.g., virtual machines). When the instances are no longer needed, their services can be deallocated to decrease cost. However, public cloud services are usually billed over predefined time and/or usage intervals, e.g., per hour, per GB of I/O. Thus, it might not be cost efficient to scale-in public cloud applications at any moment in time, without considering their billing cycles. In this work we aid developers of scalable applications for public clouds to monitor their costs, and develop cost-aware scalability controllers. We introduce a model for capturing the pricing schemes of cloud services. Based on the model we determine and evaluate the application's costs depending on its used cloud services and their billing cycles. We further evaluate cost efficiency of cloud applications, analyzing which application component is cost efficient to deallocate and when. We integrate our approach in a platform for cost-aware scalability of applications running in public clouds. We evaluate our approach on a scalable platform for IoT, deployed in Flexiant, one of the leading European public cloud providers. We show that cost-aware scalability can achieve higher application stability and performance, while reducing its operation costs.

Cost-aware scalability of applications in public clouds from Daniel Moldovan

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0 On Analyzing Elasticity Relationships �of �Cloud Services /slideshow/daniel-moldovan-cloudcom2014-slideshare/43661625 danielmoldovancloudcom2014-slideshare-150119082226-conversion-gate01
Presentation given in 6'th International Conference on Cloud Computing, CloudCom, IEEE, Singapore, 15-18 December, 2014 With the increasing cloud popularity, substantial effort has been paid for the development of emerging elastic cloud services, consisting of different units distributed among virtual machines/containers in different clouds. Due to the software stack and deployment complexity in single and multi-cloud scenarios, developing and managing such services is impeded by a lack of tools and techniques for understanding the elasticity relationships among individual service units, which influence the service's overall elasticity. In this paper we characterize the elasticity relationships, and develop mechanisms for analyzing them, based on service monitoring information and elasticity requirements. From collected monitoring information we abstract the elasticity behavior of the whole cloud service and individual units, over which we design a customizable algorithm for relationships analysis. We illustrate our approach via several experiments with an elastic data service for M2M platforms, highlighting the importance of determining elasticity relationships for the development and operation of elastic services.]]>
Presentation given in 6'th International Conference on Cloud Computing, CloudCom, IEEE, Singapore, 15-18 December, 2014 With the increasing cloud popularity, substantial effort has been paid for the development of emerging elastic cloud services, consisting of different units distributed among virtual machines/containers in different clouds. Due to the software stack and deployment complexity in single and multi-cloud scenarios, developing and managing such services is impeded by a lack of tools and techniques for understanding the elasticity relationships among individual service units, which influence the service's overall elasticity. In this paper we characterize the elasticity relationships, and develop mechanisms for analyzing them, based on service monitoring information and elasticity requirements. From collected monitoring information we abstract the elasticity behavior of the whole cloud service and individual units, over which we design a customizable algorithm for relationships analysis. We illustrate our approach via several experiments with an elastic data service for M2M platforms, highlighting the importance of determining elasticity relationships for the development and operation of elastic services.]]> Mon, 19 Jan 2015 08:22:26 GMT /slideshow/daniel-moldovan-cloudcom2014-slideshare/43661625 moldovanus@slideshare.net(moldovanus) On Analyzing Elasticity Relationships �of �Cloud Services moldovanus Presentation given in 6'th International Conference on Cloud Computing, CloudCom, IEEE, Singapore, 15-18 December, 2014 With the increasing cloud popularity, substantial effort has been paid for the development of emerging elastic cloud services, consisting of different units distributed among virtual machines/containers in different clouds. Due to the software stack and deployment complexity in single and multi-cloud scenarios, developing and managing such services is impeded by a lack of tools and techniques for understanding the elasticity relationships among individual service units, which influence the service's overall elasticity. In this paper we characterize the elasticity relationships, and develop mechanisms for analyzing them, based on service monitoring information and elasticity requirements. From collected monitoring information we abstract the elasticity behavior of the whole cloud service and individual units, over which we design a customizable algorithm for relationships analysis. We illustrate our approach via several experiments with an elastic data service for M2M platforms, highlighting the importance of determining elasticity relationships for the development and operation of elastic services. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/danielmoldovancloudcom2014-slideshare-150119082226-conversion-gate01-thumbnail.jpg?width=120&height=120&fit=bounds" /> Presentation given in 6'th International Conference on Cloud Computing, CloudCom, IEEE, Singapore, 15-18 December, 2014 With the increasing cloud popularity, substantial effort has been paid for the development of emerging elastic cloud services, consisting of different units distributed among virtual machines/containers in different clouds. Due to the software stack and deployment complexity in single and multi-cloud scenarios, developing and managing such services is impeded by a lack of tools and techniques for understanding the elasticity relationships among individual service units, which influence the service's overall elasticity. In this paper we characterize the elasticity relationships, and develop mechanisms for analyzing them, based on service monitoring information and elasticity requirements. From collected monitoring information we abstract the elasticity behavior of the whole cloud service and individual units, over which we design a customizable algorithm for relationships analysis. We illustrate our approach via several experiments with an elastic data service for M2M platforms, highlighting the importance of determining elasticity relationships for the development and operation of elastic services.

On Analyzing Elasticity Relationships of Cloud Services from Daniel Moldovan

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0 QUELLE - a Framework for Accelerating the Development of Elastic Systems /moldovanus/esocc-annotated esocc-annotated-140904095710-phpapp01
Presentation given in Third European Conference on Service-Oriented and Cloud Computing (http://esocc2014.cs.manchester.ac.uk/), 2-4 September, Manchester, United Kingdom A large number of cloud providers offer diverse types of cloud services for constructing complex "cloud-native" software. However, there is a lack of supporting tools and mechanisms for accelerating the development of cloud-native software-defined elastic systems (SESs) based on elasticity capabilities of cloud services. We introduce QUELLE -- a framework for evaluating and recommending SES deployment configurations. QUELLE presents models for describing the elasticity capabilities of cloud services and capturing elasticity requirements of SESs. Based on that QUELLE introduces novel functions and algorithms for quantifying the elasticity capabilities of cloud services. QUELLE's algorithms can recommend SES deployment configurations from cloud services that both provide the required elasticity, and fulfill cost, quality, and resource requirements, and thus can be incorporated into different phases of the development of SESs. ]]>
Presentation given in Third European Conference on Service-Oriented and Cloud Computing (http://esocc2014.cs.manchester.ac.uk/), 2-4 September, Manchester, United Kingdom A large number of cloud providers offer diverse types of cloud services for constructing complex "cloud-native" software. However, there is a lack of supporting tools and mechanisms for accelerating the development of cloud-native software-defined elastic systems (SESs) based on elasticity capabilities of cloud services. We introduce QUELLE -- a framework for evaluating and recommending SES deployment configurations. QUELLE presents models for describing the elasticity capabilities of cloud services and capturing elasticity requirements of SESs. Based on that QUELLE introduces novel functions and algorithms for quantifying the elasticity capabilities of cloud services. QUELLE's algorithms can recommend SES deployment configurations from cloud services that both provide the required elasticity, and fulfill cost, quality, and resource requirements, and thus can be incorporated into different phases of the development of SESs. ]]> Thu, 04 Sep 2014 09:57:10 GMT /moldovanus/esocc-annotated moldovanus@slideshare.net(moldovanus) QUELLE - a Framework for Accelerating the Development of Elastic Systems moldovanus Presentation given in Third European Conference on Service-Oriented and Cloud Computing (http://esocc2014.cs.manchester.ac.uk/), 2-4 September, Manchester, United Kingdom A large number of cloud providers offer diverse types of cloud services for constructing complex "cloud-native" software. However, there is a lack of supporting tools and mechanisms for accelerating the development of cloud-native software-defined elastic systems (SESs) based on elasticity capabilities of cloud services. We introduce QUELLE -- a framework for evaluating and recommending SES deployment configurations. QUELLE presents models for describing the elasticity capabilities of cloud services and capturing elasticity requirements of SESs. Based on that QUELLE introduces novel functions and algorithms for quantifying the elasticity capabilities of cloud services. QUELLE's algorithms can recommend SES deployment configurations from cloud services that both provide the required elasticity, and fulfill cost, quality, and resource requirements, and thus can be incorporated into different phases of the development of SESs. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/esocc-annotated-140904095710-phpapp01-thumbnail.jpg?width=120&height=120&fit=bounds" /> Presentation given in Third European Conference on Service-Oriented and Cloud Computing (http://esocc2014.cs.manchester.ac.uk/), 2-4 September, Manchester, United Kingdom A large number of cloud providers offer diverse types of cloud services for constructing complex "cloud-native" software. However, there is a lack of supporting tools and mechanisms for accelerating the development of cloud-native software-defined elastic systems (SESs) based on elasticity capabilities of cloud services. We introduce QUELLE -- a framework for evaluating and recommending SES deployment configurations. QUELLE presents models for describing the elasticity capabilities of cloud services and capturing elasticity requirements of SESs. Based on that QUELLE introduces novel functions and algorithms for quantifying the elasticity capabilities of cloud services. QUELLE's algorithms can recommend SES deployment configurations from cloud services that both provide the required elasticity, and fulfill cost, quality, and resource requirements, and thus can be incorporated into different phases of the development of SESs.

QUELLE - a Framework for Accelerating the Development of Elastic Systems from Daniel Moldovan

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0 Novel Models and Techniques for Monitoring and Analysis of Software-defined Elastic Systems -- SummerSOC 2014 /slideshow/homedanieltuwiendesktopdanielmoldovansummersoc2014phdsessionpptxh/36591997 danielmoldovansummersoc2014phdsession-140703075413-phpapp01
Presentation given in PhD Session of advanced School on Service Oriented Computing 30 June – 5 July, 2014, Hersonissos Crete Greece (http://www.summersoc.eu/program/) Contains in last slide embedded video of the given talk. Overview of techniques for analyzing elasticity of both cloud offered services and running cloud services, towards supporting the design, and control of elastic cloud services.]]>
Presentation given in PhD Session of advanced School on Service Oriented Computing 30 June – 5 July, 2014, Hersonissos Crete Greece (http://www.summersoc.eu/program/) Contains in last slide embedded video of the given talk. Overview of techniques for analyzing elasticity of both cloud offered services and running cloud services, towards supporting the design, and control of elastic cloud services.]]> Thu, 03 Jul 2014 07:54:13 GMT /slideshow/homedanieltuwiendesktopdanielmoldovansummersoc2014phdsessionpptxh/36591997 moldovanus@slideshare.net(moldovanus) Novel Models and Techniques for Monitoring and Analysis of Software-defined Elastic Systems -- SummerSOC 2014 moldovanus Presentation given in PhD Session of advanced School on Service Oriented Computing 30 June – 5 July, 2014, Hersonissos Crete Greece (http://www.summersoc.eu/program/) Contains in last slide embedded video of the given talk. Overview of techniques for analyzing elasticity of both cloud offered services and running cloud services, towards supporting the design, and control of elastic cloud services. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/danielmoldovansummersoc2014phdsession-140703075413-phpapp01-thumbnail.jpg?width=120&height=120&fit=bounds" /> Presentation given in PhD Session of advanced School on Service Oriented Computing 30 June – 5 July, 2014, Hersonissos Crete Greece (http://www.summersoc.eu/program/) Contains in last slide embedded video of the given talk. Overview of techniques for analyzing elasticity of both cloud offered services and running cloud services, towards supporting the design, and control of elastic cloud services.

Novel Models and Techniques for Monitoring and Analysis of Software-defined Elastic Systems -- SummerSOC 2014 from Daniel Moldovan

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0 MELA: Monitoring and Analyzing Elasticity of Cloud Services -- CloudCom 2013 /moldovanus/mela-monitoring-and-analyzing-elasticity-of-cloud-services melamonitoringandanalyzingelasticityofcloudservices-cloudcom-annotated-131203084701-phpapp01
Cloud computing has enabled a wide array of applications to be exposed as elastic cloud services. While the number of such services has rapidly increased, there is a lack of techniques for supporting cross-layered multi-level monitoring and analysis of elastic service behavior. In this paper we introduce novel concepts, namely elasticity space and elasticity pathway, for understanding elasticity of cloud services, and techniques for monitoring and evaluating them. We present MELA, a customizable framework that enables service providers and developers to analyze cross-layered, multi-level elasticity of cloud services, from the whole cloud service to service units, based on service structure dependencies. Besides support for real-time elasticity analysis of cloud service behavior, MELA provides several customizable features for extracting functions and patterns that characterize that behavior. To illustrate the usefulness of MELA, we conduct several experiments with a realistic data-as-a-service in an M2M cloud platform. Prototype and Demos at http://tuwiendsg.github.io/MELA/ Paper DOI: http://dx.doi.org/10.1109/CloudCom.2013.18]]>
Cloud computing has enabled a wide array of applications to be exposed as elastic cloud services. While the number of such services has rapidly increased, there is a lack of techniques for supporting cross-layered multi-level monitoring and analysis of elastic service behavior. In this paper we introduce novel concepts, namely elasticity space and elasticity pathway, for understanding elasticity of cloud services, and techniques for monitoring and evaluating them. We present MELA, a customizable framework that enables service providers and developers to analyze cross-layered, multi-level elasticity of cloud services, from the whole cloud service to service units, based on service structure dependencies. Besides support for real-time elasticity analysis of cloud service behavior, MELA provides several customizable features for extracting functions and patterns that characterize that behavior. To illustrate the usefulness of MELA, we conduct several experiments with a realistic data-as-a-service in an M2M cloud platform. Prototype and Demos at http://tuwiendsg.github.io/MELA/ Paper DOI: http://dx.doi.org/10.1109/CloudCom.2013.18]]> Tue, 03 Dec 2013 08:47:01 GMT /moldovanus/mela-monitoring-and-analyzing-elasticity-of-cloud-services moldovanus@slideshare.net(moldovanus) MELA: Monitoring and Analyzing Elasticity of Cloud Services -- CloudCom 2013 moldovanus Cloud computing has enabled a wide array of applications to be exposed as elastic cloud services. While the number of such services has rapidly increased, there is a lack of techniques for supporting cross-layered multi-level monitoring and analysis of elastic service behavior. In this paper we introduce novel concepts, namely elasticity space and elasticity pathway, for understanding elasticity of cloud services, and techniques for monitoring and evaluating them. We present MELA, a customizable framework that enables service providers and developers to analyze cross-layered, multi-level elasticity of cloud services, from the whole cloud service to service units, based on service structure dependencies. Besides support for real-time elasticity analysis of cloud service behavior, MELA provides several customizable features for extracting functions and patterns that characterize that behavior. To illustrate the usefulness of MELA, we conduct several experiments with a realistic data-as-a-service in an M2M cloud platform. Prototype and Demos at http://tuwiendsg.github.io/MELA/ Paper DOI: http://dx.doi.org/10.1109/CloudCom.2013.18 <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/melamonitoringandanalyzingelasticityofcloudservices-cloudcom-annotated-131203084701-phpapp01-thumbnail.jpg?width=120&height=120&fit=bounds" /> Cloud computing has enabled a wide array of applications to be exposed as elastic cloud services. While the number of such services has rapidly increased, there is a lack of techniques for supporting cross-layered multi-level monitoring and analysis of elastic service behavior. In this paper we introduce novel concepts, namely elasticity space and elasticity pathway, for understanding elasticity of cloud services, and techniques for monitoring and evaluating them. We present MELA, a customizable framework that enables service providers and developers to analyze cross-layered, multi-level elasticity of cloud services, from the whole cloud service to service units, based on service structure dependencies. Besides support for real-time elasticity analysis of cloud service behavior, MELA provides several customizable features for extracting functions and patterns that characterize that behavior. To illustrate the usefulness of MELA, we conduct several experiments with a realistic data-as-a-service in an M2M cloud platform. Prototype and Demos at http://tuwiendsg.github.io/MELA/ Paper DOI: http://dx.doi.org/10.1109/CloudCom.2013.18

MELA: Monitoring and Analyzing Elasticity of Cloud Services -- CloudCom 2013 from Daniel Moldovan

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0 https://cdn.slidesharecdn.com/profile-photo-moldovanus-48x48.jpg?cb=1614783001 I am a research assistant at the Distributed Systems Group, Institute of Information Systems, Vienna University of Technology. I have received my PhD (Dr. tech.) degree from TU Wien, Faculty of Informatics. I am working on monitoring, analysis, and control of distributed systems from enterprise to cloud-based and IoT applications, with special interests in latest IT advancements in computing models, languages, and technologies. www.infosys.tuwien.ac.at/staff/dmoldovan/ https://cdn.slidesharecdn.com/ss_thumbnails/danielmoldovancostannotated-160413123810-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/costaware-scalability-of-applications-in-public-clouds/60863481 Cost-aware scalability... https://cdn.slidesharecdn.com/ss_thumbnails/danielmoldovancloudcom2014-slideshare-150119082226-conversion-gate01-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/daniel-moldovan-cloudcom2014-slideshare/43661625 On Analyzing Elasticit... https://cdn.slidesharecdn.com/ss_thumbnails/esocc-annotated-140904095710-phpapp01-thumbnail.jpg?width=320&height=320&fit=bounds moldovanus/esocc-annotated QUELLE - a Framework f...