The Experts below are selected from a list of 42885 Experts worldwide ranked by ideXlab platform
A P Zwart - One of the best experts on this subject based on the ideXlab platform.
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Sojourn time asymptotics in processor sharing queues
2006Co-Authors: Regina Egorova, Michel Mandjes, A P ZwartAbstract:htmlabstractThis paper addresses the sojourn time asymptotics for a GI/GI/• queue operating under the Processor Sharing (PS) discipline with stochastically Varying Service rate. Our focus is on the logarithmic estimates of the tail of sojourn-time distribution, under the assumption that the jobsize distribution has a light tail. Whereas upper bounds on the decay rate can be derived under fairly general conditions, the establishment of the corresponding lower bounds requires that the Service process satisfies a samplepath large-deviation principle. We show that the class of allowed Service processes includes the case where the Service rate is modulated by a Markov process. Finally, we extend our results to a similar system operation under the Discriminatory Processor Sharing (DPS) discipline. Our analysis relies predominantly on large-deviations techniques.
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the impact of the Service discipline on delay asymptotics
Performance Evaluation, 2003Co-Authors: Sem Borst, Rudesindo Nunezqueija, Onno J. Boxma, A P ZwartAbstract:This paper surveys the M/G/1 queue with regularly Varying Service requirement distribution. It studies the effect of the Service discipline on the tail behavior of the waiting-time and/or sojourn-time distribution, demonstrating that different disciplines lead to quite different tail behavior. The orientation of the paper is methodological: We outline four different methods for determining tail behavior, illustrating them for Service disciplines like FCFS, Processor Sharing and LCFS.
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Tail Asymptotics for the Busy Period in the GI/G/1 Queue
Mathematics of Operations Research, 2001Co-Authors: A P ZwartAbstract:We characterise the tail behaviour of the busy period distribution in theGI/ G/1 queue under the assumption that the tail of the Service time distribution is of intermediate regular variation. This extends a result of de Meyer and Teugels (de Meyer and Teugels 1980), who treated theM/ G/1 queue with a regularly Varying Service time distribution. Our method of proof is, opposed to the one in de Meyer and Teugels (1980), probabilistic, and reveals an insightful relationship between the busy period and the cycle maximum.
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Tail asymptotics for the busy period in the G1/G1 queue
1999Co-Authors: A P ZwartAbstract:We characterise the tail behaviour of the busy period distribution in the GI/G/1 queue under the assumption that the tail of the Service time distribution is of intermediate regular variation. This extends a result of De Meyer and Teugels [16] who treated the M/G/1 queue with a regularly Varying Service time distribution. Our method of proof is, opposed to the one in [16], probabilistic and reveals an insightful relationship between the busy period and the cycle maximum.
Nunez R Queija - One of the best experts on this subject based on the ideXlab platform.
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heavy tails the effect of the Service discipline
Lecture Notes in Computer Science, 2002Co-Authors: Sem Borst, Onno J. Boxma, Nunez R QueijaAbstract:This paper considers the M/G/1 queue with regularly Varying Service requirement distribution. It studies the effect of the Service discipline on the tail behavior of the waiting- or sojourn time distribution, demonstrating that different disciplines may lead to quite different tail behavior. The orientation of the paper is methodological: We outline three different methods of determining tail behavior, illustrating them for Service disciplines like FCFS, Processor Sharing and LCFS.
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a queueing model with Varying Service rate for abr
Lecture Notes in Computer Science, 1998Co-Authors: Nunez R QueijaAbstract:In this paper we study a queueing model with a server that changes its Service rate according to a finite birth and death process. The object of interest is the simultaneous distribution of the number of customers in the system and the state of the server in steady-state. Both infinite and finite storage capacity for customers is considered. The influence of the operating time-scale is investigated by letting the underlying birth-death process move infinitely fast as well as infinitely slow. The model can be applied to the performance analysis of (low priority) Available Bit Rate (ABR) traffic at an ATM switch in the presence of traffic with a higher priority such as Variable Bit Rate (VBR) traffic and Constant Bit Rate (CBR) traffic. For a specific example we illustrate by numerical experiments the influence of the latter traffic types on the ABR Service.
Sem Borst - One of the best experts on this subject based on the ideXlab platform.
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Tail asymptotics for discriminatory processor-sharing queues with heavy-tailed Service requirements
Performance Evaluation, 2005Co-Authors: Sem Borst, Dennis Van Ooteghem, Bert ZwartAbstract:We derive the sojourn time asymptotics for a multi-class GI/GI/1 queue with regularly Varying Service requirements operating under the discriminatory processor-sharing (DPS) discipline. DPS provides a natural approach for modelling the flow-level performance of differentiated bandwidth-sharing mechanisms. Under certain assumptions, we prove that the Service requirement and sojourn time of a given class have similar tail behaviour, independent of the specific values of the DPS weights. As a by-product, we obtain an extension of the tail equivalence for ordinary processor-sharing (PS) queues to non-Poisson arrivals. The results suggest that DPS offers a potential instrument for effectuating preferential treatment to high-priority classes, without inflicting excessive delays on low-priority classes. To obtain the asymptotics, we develop a novel method which only involves information of the workload process and does not require any knowledge of the steady-state queue length distribution. In particular, the proof method brings sufficient strength to extend the results to scenarios with a time-Varying Service capacity.
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the impact of the Service discipline on delay asymptotics
Performance Evaluation, 2003Co-Authors: Sem Borst, Rudesindo Nunezqueija, Onno J. Boxma, A P ZwartAbstract:This paper surveys the M/G/1 queue with regularly Varying Service requirement distribution. It studies the effect of the Service discipline on the tail behavior of the waiting-time and/or sojourn-time distribution, demonstrating that different disciplines lead to quite different tail behavior. The orientation of the paper is methodological: We outline four different methods for determining tail behavior, illustrating them for Service disciplines like FCFS, Processor Sharing and LCFS.
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heavy tails the effect of the Service discipline
Lecture Notes in Computer Science, 2002Co-Authors: Sem Borst, Onno J. Boxma, Nunez R QueijaAbstract:This paper considers the M/G/1 queue with regularly Varying Service requirement distribution. It studies the effect of the Service discipline on the tail behavior of the waiting- or sojourn time distribution, demonstrating that different disciplines may lead to quite different tail behavior. The orientation of the paper is methodological: We outline three different methods of determining tail behavior, illustrating them for Service disciplines like FCFS, Processor Sharing and LCFS.
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Computer Performance Evaluation / TOOLS - Heavy Tails: The Effect of the Service Discipline
Computer Performance Evaluation: Modelling Techniques and Tools, 2002Co-Authors: Sem Borst, Onno Boxma, R. Núñez QueijaAbstract:This paper considers the M/G/1 queue with regularly Varying Service requirement distribution. It studies the effect of the Service discipline on the tail behavior of the waiting- or sojourn time distribution, demonstrating that different disciplines may lead to quite different tail behavior. The orientation of the paper is methodological: We outline three different methods of determining tail behavior, illustrating them for Service disciplines like FCFS, Processor Sharing and LCFS.
Manoj Nambiar - One of the best experts on this subject based on the ideXlab platform.
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Performance Modeling of Multi-tiered Web Applications with Varying Service Demands
International Journal of Networking and Computing, 2016Co-Authors: Ajay Kattepur, Manoj NambiarAbstract:Multi-tiered transactional web applications are frequently used in IT enterprise based systems. Due to their inherent distributed nature, pre-deployment testing for high-availability and Varying concurrency are important for post-deployment performance. Accurate performance modeling of such applications can help estimate values for future deployment variations as well as validate experimental results. In order to theoretically model performance of multi-tiered applications, we use queuing networks and Mean Value Analysis (MVA) models. While MVA has been shown to work well with closed queuing networks, there are particular limitations in cases where the Service demands vary with concurrency. This variation of Service demands for various resources (CPU, Disk, Network) is demonstrated through multiple experiments. This is further contrived by the use of multi-server queues in multi-core CPUs, that are not traditionally captured in MVA. We compare performance of a multi-server MVA model alongside actual performance testing measurements and demonstrate this deviation. Using spline interpolation of collected Service demands, we show that a modified version of the MVA algorithm (called MVASD ) that accepts an array of Service demands, can provide superior estimates of maximum throughput and response time. Results are demonstrated over multi-tier vehicle insurance registration and e-commerce web applications. The mean deviations of predicted throughput and response time are shown to be less the 3% and 9% , respectively. Additionally, we analyze the effect of spline interpolation of Service demands as a function of throughput on the prediction results. Using Chebyshev Nodes , the tradeoff between the number of test points and the spline interpolation/prediction accuracy is also studied.Â
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Performance Modeling of Multi-tiered Web Applications with Varying Service Demands
2015Co-Authors: Ajay Kattepur, Manoj NambiarAbstract:Multi-tiered transactional web applications are frequently used in enterprise based systems. Due to their inherent distributed nature, pre-deployment testing for high-availability and Varying concurrency are important for post-deployment performance. Accurate performance modeling of such applications can help estimate values for future deployment variations as well as validate experimental results. In order to theoretically model performance of multi-tiered applications, we use queuing networks and Mean Value Analysis (MVA) models. While MVA has been shown to work well with closed queuing networks, there are particular limitations in cases where the Service demands vary with concurrency. This is further contrived by the use of multi-server queues in multi-core CPUs, that are not traditionally captured in MVA. We compare performance of a multi-server MVA model along-side actual performance testing measurements and demonstrate this deviation. Using spline interpolation of collected Service demands, we show that a modified version of the MVA algorithm (called MVASD) that accepts an array of Service demands, can provide superior estimates of maximum throughput and response time. Results are demonstrated over multi-tier vehicle insurance registration and e-commerce web applications. The mean deviations of predicted throughput and response time are shown to be less the 3% and 9%, respectively. Additionally, we analyze the effect of spline interpolation of Service demands as a function of throughput on the prediction results.
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IPDPS Workshops - Performance Modeling of Multi-tiered Web Applications with Varying Service Demands
2015 IEEE International Parallel and Distributed Processing Symposium Workshop, 2015Co-Authors: Ajay Kattepur, Manoj NambiarAbstract:Multi-tiered transactional web applications are frequently used in enterprise based systems. Due to their inherent distributed nature, pre-deployment testing for high-availability and Varying concurrency are important for post-deployment performance. Accurate performance modeling of such applications can help estimate values for future deployment variations as well as validate experimental results. In order to theoretically model performance of multi-tiered applications, we use queuing networks and Mean Value Analysis (MVA) models. While MVA has been shown to work well with closed queuing networks, there are particular limitations in cases where the Service demands vary with concurrency. This is further contrived by the use of multi-server queues in multi-core CPUs, that are not traditionally captured in MVA. We compare performance of a multi-server MVA model alongside actual performance testing measurements and demonstrate this deviation. Using spline interpolation of collected Service demands, we show that a modified version of the MVA algorithm (called MVASD) that accepts an array of Service demands, can provide superior estimates of maximum throughput and response time. Results are demonstrated over multi-tier vehicle insurance registration and e-commerce web applications. The mean deviations of predicted throughput and response time are shown to be less the 3% and 9%, respectively. Additionally, we analyze the effect of spline interpolation of Service demands as a function of throughput on the prediction results.
Ajay Kattepur - One of the best experts on this subject based on the ideXlab platform.
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Performance Modeling of Multi-tiered Web Applications with Varying Service Demands
International Journal of Networking and Computing, 2016Co-Authors: Ajay Kattepur, Manoj NambiarAbstract:Multi-tiered transactional web applications are frequently used in IT enterprise based systems. Due to their inherent distributed nature, pre-deployment testing for high-availability and Varying concurrency are important for post-deployment performance. Accurate performance modeling of such applications can help estimate values for future deployment variations as well as validate experimental results. In order to theoretically model performance of multi-tiered applications, we use queuing networks and Mean Value Analysis (MVA) models. While MVA has been shown to work well with closed queuing networks, there are particular limitations in cases where the Service demands vary with concurrency. This variation of Service demands for various resources (CPU, Disk, Network) is demonstrated through multiple experiments. This is further contrived by the use of multi-server queues in multi-core CPUs, that are not traditionally captured in MVA. We compare performance of a multi-server MVA model alongside actual performance testing measurements and demonstrate this deviation. Using spline interpolation of collected Service demands, we show that a modified version of the MVA algorithm (called MVASD ) that accepts an array of Service demands, can provide superior estimates of maximum throughput and response time. Results are demonstrated over multi-tier vehicle insurance registration and e-commerce web applications. The mean deviations of predicted throughput and response time are shown to be less the 3% and 9% , respectively. Additionally, we analyze the effect of spline interpolation of Service demands as a function of throughput on the prediction results. Using Chebyshev Nodes , the tradeoff between the number of test points and the spline interpolation/prediction accuracy is also studied.Â
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Performance Modeling of Multi-tiered Web Applications with Varying Service Demands
2015Co-Authors: Ajay Kattepur, Manoj NambiarAbstract:Multi-tiered transactional web applications are frequently used in enterprise based systems. Due to their inherent distributed nature, pre-deployment testing for high-availability and Varying concurrency are important for post-deployment performance. Accurate performance modeling of such applications can help estimate values for future deployment variations as well as validate experimental results. In order to theoretically model performance of multi-tiered applications, we use queuing networks and Mean Value Analysis (MVA) models. While MVA has been shown to work well with closed queuing networks, there are particular limitations in cases where the Service demands vary with concurrency. This is further contrived by the use of multi-server queues in multi-core CPUs, that are not traditionally captured in MVA. We compare performance of a multi-server MVA model along-side actual performance testing measurements and demonstrate this deviation. Using spline interpolation of collected Service demands, we show that a modified version of the MVA algorithm (called MVASD) that accepts an array of Service demands, can provide superior estimates of maximum throughput and response time. Results are demonstrated over multi-tier vehicle insurance registration and e-commerce web applications. The mean deviations of predicted throughput and response time are shown to be less the 3% and 9%, respectively. Additionally, we analyze the effect of spline interpolation of Service demands as a function of throughput on the prediction results.
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IPDPS Workshops - Performance Modeling of Multi-tiered Web Applications with Varying Service Demands
2015 IEEE International Parallel and Distributed Processing Symposium Workshop, 2015Co-Authors: Ajay Kattepur, Manoj NambiarAbstract:Multi-tiered transactional web applications are frequently used in enterprise based systems. Due to their inherent distributed nature, pre-deployment testing for high-availability and Varying concurrency are important for post-deployment performance. Accurate performance modeling of such applications can help estimate values for future deployment variations as well as validate experimental results. In order to theoretically model performance of multi-tiered applications, we use queuing networks and Mean Value Analysis (MVA) models. While MVA has been shown to work well with closed queuing networks, there are particular limitations in cases where the Service demands vary with concurrency. This is further contrived by the use of multi-server queues in multi-core CPUs, that are not traditionally captured in MVA. We compare performance of a multi-server MVA model alongside actual performance testing measurements and demonstrate this deviation. Using spline interpolation of collected Service demands, we show that a modified version of the MVA algorithm (called MVASD) that accepts an array of Service demands, can provide superior estimates of maximum throughput and response time. Results are demonstrated over multi-tier vehicle insurance registration and e-commerce web applications. The mean deviations of predicted throughput and response time are shown to be less the 3% and 9%, respectively. Additionally, we analyze the effect of spline interpolation of Service demands as a function of throughput on the prediction results.
