Software bottlenecking in client-server systems and rendezvous networks

Neilson, J. E.; Woodside, C. Murray; Petriu, Dorina C.; Majumdar, Shikharesh

doi:10.1109/32.464543

Cited by 76 publications

(44 citation statements)

References 10 publications

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“…A performance bottleneck at the processor, for example, can be alleviated by executing the server process on a faster CPU. Sometimes the bottleneck that limits system performance is a saturated server process rather than the processor on which it executes [8,24]. Such a software bottleneck may occur when the server process is``busy'' almost 1000 of the time (either executing or waiting for responses from other servers) but the processor on which it executes is not heavily utilized.…”

Section: Introductionmentioning

confidence: 97%

“…Such a software bottleneck may occur when the server process is``busy'' almost 1000 of the time (either executing or waiting for responses from other servers) but the processor on which it executes is not heavily utilized. Multithreading of the server has been suggested in the literature for stretching these software bottlenecks [24]. The impact of client agent server interaction architecture on the performance of a CORBA-based system is analyzed in [1].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Performance of Scheduling Strategies for Client–Server Systems

Graham¹,

Majumdar

1999

Journal of Parallel and Distributed Computing

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Section: Introductionmentioning

confidence: 97%

Section: Introductionmentioning

confidence: 99%

Performance of Scheduling Strategies for Client–Server Systems

Graham¹,

Majumdar

1999

Journal of Parallel and Distributed Computing

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“…Formalisms such as Layered Queueing Networks [14] and IMC [4] countered this with built-in multi-phase behaviour within the synchronisation [15]. Other formalisms such as semi-Markov SPNs [16] and semi-Markov SPAs [17] used a more general underlying stochastic model, but this restricted the ability of the modeller to cope with concurrency; a critical feature of most modern-day applications.…”

Section: Introductionmentioning

confidence: 99%

Shared Transaction Markov Chains for fluid analysis of massively parallel systems

Hayden

Bradley

2009

2009 IEEE International Symposium on Modeling, Analysis &Amp; Simulation of Computer and Telecommunication Systems

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Abstract-We introduce a low-level performance modelling formalism, Shared Transaction Markov Chains (STMCs), specifically designed for the capture and analysis of massively parallel stochastic systems through fluid techniques. We introduce the notion of a shared transaction between concurrently running Markov chains which allows a multi-phase synchronisation to accurately represent complex cooperation between modelling components in a compositional manner. We demonstrate the new modelling formalism on four distinct models and show how fluid analysis may be performed, with results, where appropriate. Our contribution is that this is the first such system tailored to the fluid performance analysis of transaction-based systems as found in computing applications such as peer-to-peer networks, web architectures and Publish-Subscribe networks. The second contribution is that STMCs permit composed phase-type distributed synchronisation which is more useful from a transaction modelling perspective.

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“…An analytical model of server systems based on Layered Queuing Networks (LQN) was proposed in [20]. A more general analytical model of client-server systems based on rendezvous networks was given in [21]. It illustrates how certain slow servers could become bottlenecks and suggests threading/cloning to relieve these bottlenecks.…”

Section: The Scalability Modelmentioning

confidence: 99%

Scaling a Shared Object Space to the Internet: Case Study of Virat.

Srinivas¹,

D²

2006

JOT

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Scalability is an important issue in the construction of distributed systems. Shared object spaces provide an elegant and easy-to program abstraction for building applications. However, existing shared object spaces have been realized at the cluster level. Use of centralized components, lack of effective failure handling mechanisms, lack of efficient object lookup mechanisms as well as consistency maintenance are the key issues that inhibit scalability of existing shared object spaces. We present the case study of scaling an existing shared object space (Virat) to the Internet. Bottlenecks in Virat include the granularity of consistency maintenance and Object Meta-data Repository (OMR) failures. Both the design and implementation of Virat has been modified in order to increase the granularity at which consistency is maintained. Virat has also been redesigned such that the OMRs form a Peer-to-Peer (P2P) overlay in order to handle OMR failures and improve scalability. Experimental evaluations are presented to show that the optimized version of Virat scales better, especially over a wide-area network. In addition, this paper also explains how to develop applications over the shared object space, with code sketches.

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Software bottlenecking in client-server systems and rendezvous networks

Cited by 76 publications

References 10 publications

Performance of Scheduling Strategies for Client–Server Systems

Performance of Scheduling Strategies for Client–Server Systems

Shared Transaction Markov Chains for fluid analysis of massively parallel systems

Scaling a Shared Object Space to the Internet: Case Study of Virat.

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