2008
DOI: 10.1145/1384529.1375460
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Bound analysis of closed queueing networks with workload burstiness

Abstract: Burstiness and temporal dependence in service processes are often found in multi-tier architectures and storage devices and must be captured accurately in capacity planning models as these features are responsible of significant performance degradations. However, existing models and approximations for networks of first-come firstserved (FCFS) queues with general independent (GI) service are unable to predict performance of systems with temporal dependence in workloads.To overcome this difficulty, we define and… Show more

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Cited by 12 publications
(5 citation statements)
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“…The CTMC state is a tuple (n, k), where n is the population 2 Notice that a closed PH queueing network might be seen as a specialization of the recently proposed MAP queueing networks [7], which additionally offer the ability to consider service times that are correlated as described by a Markovian arrival process (MAP). However, such models are harder to solve and thus are less appealing for run-time applications.…”
Section: Matrix Geometric Methodsmentioning
confidence: 99%
See 1 more Smart Citation
“…The CTMC state is a tuple (n, k), where n is the population 2 Notice that a closed PH queueing network might be seen as a specialization of the recently proposed MAP queueing networks [7], which additionally offer the ability to consider service times that are correlated as described by a Markovian arrival process (MAP). However, such models are harder to solve and thus are less appealing for run-time applications.…”
Section: Matrix Geometric Methodsmentioning
confidence: 99%
“…A general methodology based on approximation to G/G/1-queues leads to the queueing network analysis proposed by Whitt [26]. More recently, work has been done in approximating networks in which arrival-or service-processes are represented by correlated Markov-modulated processes [13,25,7,9,8]. Such methods are able to evaluate more expressive models than are studied here, but typically their computational requirements are much larger than the ones we propose 1 .…”
Section: Introductionmentioning
confidence: 99%
“…In contrast, service demand burstiness can be seen as the result of serially correlated service demands placed by consecutive requests on a hardware or software system [26,23,21], rather than a feature of the interarrival times between requests. It is much harder to model and predict system performance for workloads with service demand burstiness than for traditional workloads [7]. This stresses the need for benchmarking tools that support analytic and simulation techniques to study the performance impact of service demand burstiness.…”
Section: Related Workmentioning
confidence: 99%
“…Specifically, we use a new linear programming approach that remains computationally efficient also on models with large populations and large number of servers. An extended version of the work presented here can be found in [1].…”
Section: Introductionmentioning
confidence: 99%