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Poul E Heegaard - One of the best experts on this subject based on the ideXlab platform.
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Simulation of the Response Time Distribution of fault-tolerant multi-tier cloud services
Journal of Simulation, 2017Co-Authors: Anders N Gullhav, Bjørn Nygreen, Poul E HeegaardAbstract:We are considering the problem of obtaining the Response Time Distribution of fault-tolerant multi-tier services. In the provision of software-as-a-service applications, the service provider is obliged to ensure a certain quality of service. Herein, we regard upper bounds on the Response Time. The services consist of multiple components with different functionality, which are prone to failures, and fail according to a certain failure Time Distribution. However, due to redundancy, a failure will not necessarily bring the service down, but rather increase the Response Time. A fundamental difficulty with estimating the Response Time Distribution while considering failures is related to the disparity in the Time scales of the Time between failures and service Times. To overcome this issue, we propose an approach based on a decomposition, which combines an analytic model of the failure process and a discrete event simulation model to sample the Response Time Distribution. In an experimental study, we compare this simulation-based approach with an analytic approach, and illustrate how this approach can be utilised by service providers as decision support. We also show that in certain cases, the analytic approach might provide a safe bound on the Response Time.
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approximating the Response Time Distribution of fault tolerant multi tier cloud services
IEEE ACM International Conference Utility and Cloud Computing, 2013Co-Authors: Anders N Gullhav, Bjørn Nygreen, Poul E HeegaardAbstract:Cloud services with a multi-tiered architecture are often difficult to evaluate in terms of performance and dependability. The tiered architecture complicates the resource capacity decisions of the service provider, and makes it more demanding to maintain a good balance between capacity and quality of service. In this work we present an approximation of the Response Time Distribution of a multi-tier service, which should help the providers in their planning and operation. The approximation also takes into account failures in the virtual machines in which the service runs, and acknowledges replication of the tiers. We demonstrate that the approximation can be used as decision support for service providers.
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UCC - Approximating the Response Time Distribution of Fault-Tolerant Multi-tier Cloud Services
2013 IEEE ACM 6th International Conference on Utility and Cloud Computing, 2013Co-Authors: Anders N Gullhav, Bjørn Nygreen, Poul E HeegaardAbstract:Cloud services with a multi-tiered architecture are often difficult to evaluate in terms of performance and dependability. The tiered architecture complicates the resource capacity decisions of the service provider, and makes it more demanding to maintain a good balance between capacity and quality of service. In this work we present an approximation of the Response Time Distribution of a multi-tier service, which should help the providers in their planning and operation. The approximation also takes into account failures in the virtual machines in which the service runs, and acknowledges replication of the tiers. We demonstrate that the approximation can be used as decision support for service providers.
Anders N Gullhav - One of the best experts on this subject based on the ideXlab platform.
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Simulation of the Response Time Distribution of fault-tolerant multi-tier cloud services
Journal of Simulation, 2017Co-Authors: Anders N Gullhav, Bjørn Nygreen, Poul E HeegaardAbstract:We are considering the problem of obtaining the Response Time Distribution of fault-tolerant multi-tier services. In the provision of software-as-a-service applications, the service provider is obliged to ensure a certain quality of service. Herein, we regard upper bounds on the Response Time. The services consist of multiple components with different functionality, which are prone to failures, and fail according to a certain failure Time Distribution. However, due to redundancy, a failure will not necessarily bring the service down, but rather increase the Response Time. A fundamental difficulty with estimating the Response Time Distribution while considering failures is related to the disparity in the Time scales of the Time between failures and service Times. To overcome this issue, we propose an approach based on a decomposition, which combines an analytic model of the failure process and a discrete event simulation model to sample the Response Time Distribution. In an experimental study, we compare this simulation-based approach with an analytic approach, and illustrate how this approach can be utilised by service providers as decision support. We also show that in certain cases, the analytic approach might provide a safe bound on the Response Time.
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approximating the Response Time Distribution of fault tolerant multi tier cloud services
IEEE ACM International Conference Utility and Cloud Computing, 2013Co-Authors: Anders N Gullhav, Bjørn Nygreen, Poul E HeegaardAbstract:Cloud services with a multi-tiered architecture are often difficult to evaluate in terms of performance and dependability. The tiered architecture complicates the resource capacity decisions of the service provider, and makes it more demanding to maintain a good balance between capacity and quality of service. In this work we present an approximation of the Response Time Distribution of a multi-tier service, which should help the providers in their planning and operation. The approximation also takes into account failures in the virtual machines in which the service runs, and acknowledges replication of the tiers. We demonstrate that the approximation can be used as decision support for service providers.
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UCC - Approximating the Response Time Distribution of Fault-Tolerant Multi-tier Cloud Services
2013 IEEE ACM 6th International Conference on Utility and Cloud Computing, 2013Co-Authors: Anders N Gullhav, Bjørn Nygreen, Poul E HeegaardAbstract:Cloud services with a multi-tiered architecture are often difficult to evaluate in terms of performance and dependability. The tiered architecture complicates the resource capacity decisions of the service provider, and makes it more demanding to maintain a good balance between capacity and quality of service. In this work we present an approximation of the Response Time Distribution of a multi-tier service, which should help the providers in their planning and operation. The approximation also takes into account failures in the virtual machines in which the service runs, and acknowledges replication of the tiers. We demonstrate that the approximation can be used as decision support for service providers.
Bjørn Nygreen - One of the best experts on this subject based on the ideXlab platform.
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Simulation of the Response Time Distribution of fault-tolerant multi-tier cloud services
Journal of Simulation, 2017Co-Authors: Anders N Gullhav, Bjørn Nygreen, Poul E HeegaardAbstract:We are considering the problem of obtaining the Response Time Distribution of fault-tolerant multi-tier services. In the provision of software-as-a-service applications, the service provider is obliged to ensure a certain quality of service. Herein, we regard upper bounds on the Response Time. The services consist of multiple components with different functionality, which are prone to failures, and fail according to a certain failure Time Distribution. However, due to redundancy, a failure will not necessarily bring the service down, but rather increase the Response Time. A fundamental difficulty with estimating the Response Time Distribution while considering failures is related to the disparity in the Time scales of the Time between failures and service Times. To overcome this issue, we propose an approach based on a decomposition, which combines an analytic model of the failure process and a discrete event simulation model to sample the Response Time Distribution. In an experimental study, we compare this simulation-based approach with an analytic approach, and illustrate how this approach can be utilised by service providers as decision support. We also show that in certain cases, the analytic approach might provide a safe bound on the Response Time.
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approximating the Response Time Distribution of fault tolerant multi tier cloud services
IEEE ACM International Conference Utility and Cloud Computing, 2013Co-Authors: Anders N Gullhav, Bjørn Nygreen, Poul E HeegaardAbstract:Cloud services with a multi-tiered architecture are often difficult to evaluate in terms of performance and dependability. The tiered architecture complicates the resource capacity decisions of the service provider, and makes it more demanding to maintain a good balance between capacity and quality of service. In this work we present an approximation of the Response Time Distribution of a multi-tier service, which should help the providers in their planning and operation. The approximation also takes into account failures in the virtual machines in which the service runs, and acknowledges replication of the tiers. We demonstrate that the approximation can be used as decision support for service providers.
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UCC - Approximating the Response Time Distribution of Fault-Tolerant Multi-tier Cloud Services
2013 IEEE ACM 6th International Conference on Utility and Cloud Computing, 2013Co-Authors: Anders N Gullhav, Bjørn Nygreen, Poul E HeegaardAbstract:Cloud services with a multi-tiered architecture are often difficult to evaluate in terms of performance and dependability. The tiered architecture complicates the resource capacity decisions of the service provider, and makes it more demanding to maintain a good balance between capacity and quality of service. In this work we present an approximation of the Response Time Distribution of a multi-tier service, which should help the providers in their planning and operation. The approximation also takes into account failures in the virtual machines in which the service runs, and acknowledges replication of the tiers. We demonstrate that the approximation can be used as decision support for service providers.
Francesco Quaglia - One of the best experts on this subject based on the ideXlab platform.
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accuracy versus efficiency of hyper exponential approximations of the Response Time Distribution of mmpp m 1 queues
International Journal of Parallel Emergent and Distributed Systems, 2009Co-Authors: Paolo Romano, Bruno Ciciani, Andrea Santoro, Francesco QuagliaAbstract:The Markov-Modulated Poisson Process (MMPP) has been shown to well describe the flow of incoming traffic in networked systems, such as the Grid and the WWW. This makes the MMPP/M/1 queue a valuable instrument to evaluate and predict the service level of networked servers. In a recent work, we have provided an approximate solution for the Response Time Distribution of the MMPP/M/1 queue, based on a weighted superposition of M/M/1 queues (i.e. a hyper-exponential process). In this article, we address the tradeoff between the accuracy of this approximation and its computational cost. By jointly considering both accuracy and cost, we identify the scenarios where such approximate solution could be effectively used in support of network servers (dynamic) configuration and evaluation strategies aimed at ensuring agreed dependability levels in case of, e.g. request redirection due to faults. Finally, the effectiveness of the proposed approximate solution method is evaluated for a real-world case study relying on a trace-based traffic characterisation of a Grid server.
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Accuracy versus efficiency of hyper-exponential approximations of the Response Time Distribution of MMPP/M/1 queues
International Journal of Parallel Emergent and Distributed Systems, 2009Co-Authors: Paolo Romano, Bruno Ciciani, Andrea Santoro, Francesco QuagliaAbstract:The Markov-Modulated Poisson Process (MMPP) has been shown to well describe the flow of incoming traffic in networked systems, such as the Grid and the WWW. This makes the MMPP/M/1 queue a valuable instrument to evaluate and predict the service level of networked servers. In a recent work, we have provided an approximate solution for the Response Time Distribution of the MMPP/M/1 queue, based on a weighted superposition of M/M/1 queues (i.e. a hyper-exponential process). In this article, we address the tradeoff between the accuracy of this approximation and its computational cost. By jointly considering both accuracy and cost, we identify the scenarios where such approximate solution could be effectively used in support of network servers (dynamic) configuration and evaluation strategies aimed at ensuring agreed dependability levels in case of, e.g. request redirection due to faults. Finally, the effectiveness of the proposed approximate solution method is evaluated for a real-world case study relying on a trace-based traffic characterisation of a Grid server.
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fast computation of hyper exponential approximations of the Response Time Distribution of mmpp m 1 queues
Annual Simulation Symposium, 2008Co-Authors: Paolo Romano, Bruno Ciciani, Andrea Santoro, Francesco QuagliaAbstract:Input characterization to describe the flow of incoming traffic in network systems, such as the grid and the WWW, is often performed by using Markov modulated poisson processes (MMPP). Therefore, to enact capacity planning and quality-of-service (QoS) oriented design, the model of the servers that receive the incoming traffic is often described as a MMPP/M/1 queue. In a work we have provided an approximate solution for the Response Time Distribution of the MMPP/M/1 queue, which is based on a hyper-exponential process obtained via a weighted superposition of the Response Time Distributions of M/M/l queues. Compared to exact solution methods, or simulative techniques, the aim of this approximation is to provide the potential for more efficient model solution, so to enable, e.g., real-Time what-if analysis in system reconfiguration scenarios. In this paper, we show how fast the computation can be supported in practical settings by ad-hoc techniques allowing the hyper-exponential model to be solved with no iterative or numerical costly steps, which would otherwise be required in order to compute the length of transient phases due to state switches in the MMPP arrival process. An application to the context of performance analysis of a grid system is also shown, supporting the efficiency of our proposal.
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Annual Simulation Symposium - Fast Computation of Hyper-exponential Approximations of the Response Time Distribution of MMPP/M/1 Queues
41st Annual Simulation Symposium (anss-41 2008), 2008Co-Authors: Paolo Romano, Bruno Ciciani, Andrea Santoro, Francesco QuagliaAbstract:Input characterization to describe the flow of incoming traffic in network systems, such as the grid and the WWW, is often performed by using Markov modulated poisson processes (MMPP). Therefore, to enact capacity planning and quality-of-service (QoS) oriented design, the model of the servers that receive the incoming traffic is often described as a MMPP/M/1 queue. In a work we have provided an approximate solution for the Response Time Distribution of the MMPP/M/1 queue, which is based on a hyper-exponential process obtained via a weighted superposition of the Response Time Distributions of M/M/l queues. Compared to exact solution methods, or simulative techniques, the aim of this approximation is to provide the potential for more efficient model solution, so to enable, e.g., real-Time what-if analysis in system reconfiguration scenarios. In this paper, we show how fast the computation can be supported in practical settings by ad-hoc techniques allowing the hyper-exponential model to be solved with no iterative or numerical costly steps, which would otherwise be required in order to compute the length of transient phases due to state switches in the MMPP arrival process. An application to the context of performance analysis of a grid system is also shown, supporting the efficiency of our proposal.
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IPDPS - Accuracy vs efficiency of hyper-exponential approximations of the Response Time Distribution of MMPP/M/1 queues
2008 IEEE International Symposium on Parallel and Distributed Processing, 2008Co-Authors: Paolo Romano, Bruno Ciciani, Andrea Santoro, Francesco QuagliaAbstract:The Markov modulated Poisson process (MMPP) has been shown to well describe the flow of incoming traffic in networked systems, such as the Grid and the WWW. This makes the MMPP/M/1 queue a valuable instrument to evaluate and predict the service level of networked servers. In a recent work we have provided an approximate solution for the Response Time Distribution of the MMPP/M/1 queue, which is based on a weighted superposition of M/M/l queues (i.e. a hyper-exponential process). In this article we address the tradeoff between the accuracy of this approximation and its computational cost. By jointly considering both accuracy and cost, we identify the scenarios where such approximate solution could be effectively used in support of network servers (dynamic) configuration and evaluation strategies, aimed at ensuring the agreed dependability levels in case of, e.g., request redirection due to faults.
Tadashi Dohi - One of the best experts on this subject based on the ideXlab platform.
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estimating Response Time Distribution of server application in software aging phenomenon
International Symposium on Software Reliability Engineering, 2013Co-Authors: Hiroyuki Okamura, Chao Luo, Tadashi DohiAbstract:This paper considers the estimation algorithm for Response Time Distribution of a server application under the environment where software aging occurs. We develop the continuous-Time Markov chain (CTMC) model to represent the degradation level of server and then show that the Response Time Distribution can be represented by a Markov-modulated compound Poisson process (MMCPP). The estimation algorithm for the Response Time Distribution is given by the EM algorithm for MMCPP. In a numerical example, we demonstrate the Response Time estimation for the experimental data of MySQL server.
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ISSRE (Supplemental Proceedings) - Estimating Response Time Distribution of server application in software aging phenomenon
2013 IEEE International Symposium on Software Reliability Engineering Workshops (ISSREW), 2013Co-Authors: Hiroyuki Okamura, Chao Luo, Tadashi DohiAbstract:This paper considers the estimation algorithm for Response Time Distribution of a server application under the environment where software aging occurs. We develop the continuous-Time Markov chain (CTMC) model to represent the degradation level of server and then show that the Response Time Distribution can be represented by a Markov-modulated compound Poisson process (MMCPP). The estimation algorithm for the Response Time Distribution is given by the EM algorithm for MMCPP. In a numerical example, we demonstrate the Response Time estimation for the experimental data of MySQL server.
