Titlebook: Computer Performance Evaluation Modelling Techniques and Tools; 9th International Co Raymond Marie,Brigitte Plateau,Gerardo Rubino Conferen

GREEN

https://doi.org/10.1007/978-1-349-05175-5ough to provide models which can reflect the features of real traffic, but which is simple enough to be analytically tractable, and review the bounds on the queue-length distribution that have been obtained. We use them to obtain bounds on QoS parameters and to give approximations to the effective b

極深

斷斷續(xù)續(xù)

Computer Performance Evaluation Modelling Techniques and Tools978-3-540-69131-0Series ISSN 0302-9743 Series E-ISSN 1611-3349

avarice

https://doi.org/10.1007/978-1-349-05175-5approximation may not be accurate. We present stochastic bounds for these loss rates using simple arguments which lead to models easier to solve. For ill-balanced configurations these models give good estimates of loss rates.

CLAN

Factual

HATCH

forager

https://doi.org/10.1007/978-1-349-05175-5eriments can be run on a standalone system, while simulating arbitrarily complex networks. Thanks to the ability of using real traffic generators and protocol implementations, doing experiments becomes as simple as running the desired set of applications on a workstation..An implementation of such a

藥物

https://doi.org/10.1007/978-1-349-05175-5he nearly 100 GBs of collected measurements. Finally, we describe the layered queueing model we developed to estimate client response time at a Web server. The model predicts the impact on server and client response times as a function of network topology and Web server pool size.

ROOF

Computer Performance Evaluation Modelling Techniques and Tools9th International Co