1. / Copyright © Siemens AG 2006. All rights reserved. Corporate Technology Performance Prediction of Client-Server Systems by High-Level Abstraction Models SEC(R) 2008 Presented by Alexander Pastsyak and Yana Rebrova Service Queue

2. Page 2 SEC(R) 2008 © Siemens AG, Corporate TechnologyAlexander Pastsyak, Rebrova Yana Outline  Motivation  Formalisms to describe system performance  Layered Queuing Networks (LQN)  Performance Evaluation Process Algebra (PEPA)  Queuing Petri Nets (QPN)  Architecture of the Test System  Experiments  Results  Conclusion

3. Page 3 SEC(R) 2008 © Siemens AG, Corporate TechnologyAlexander Pastsyak, Rebrova Yana Motivation in out Two place buffer Buf2 inout in Database Service Software Performance models Real systems composed from many components Application server Web server Queue

4. Page 4 SEC(R) 2008 © Siemens AG, Corporate TechnologyAlexander Pastsyak, Rebrova Yana What do we want to do? What kind of predictions can be obtained from the models for response time and throughput characteristics? What is the method to calibrate the models? How to map different system architecture entities to the model elements (build the models)?

5. Page 5 SEC(R) 2008 © Siemens AG, Corporate TechnologyAlexander Pastsyak, Rebrova Yana Used formalisms and tools Stochastic Process Algebras (SPA) Stochastic Petri Nets (SPN) Layered Queuing Networks (LQN) Formalisms QPN Modeling Environment (QPME) PEPA Workbench LQNSolver Tools ACTUALITYACTUALITY AVAILABILITYAVAILABILITY

6. Page 6 SEC(R) 2008 © Siemens AG, Corporate TechnologyAlexander Pastsyak, Rebrova Yana Formalisms: Layered Queuing Networks Request processing Queue Server Client Request Queuing Network Layered Queuing Network Request processing Queue Server1 Client Request1 Request processing Queue Server2 Request2

7. Page 7 SEC(R) 2008 © Siemens AG, Corporate TechnologyAlexander Pastsyak, Rebrova Yana LQN- Model Building Blocks Processors are used by activities within a performance model to consume time. Tasks are used in layered queuing networks to represent software resources Activities are the lowest- level of specification in the performance model. Entries service requests and are used to differentiate the service provided by a task. Service requests from one task to another Precedence is used to connect activities within a task to form an activity graph Processors Tasks Entries Activities RequestsPrecedence

8. Page 8 SEC(R) 2008 © Siemens AG, Corporate TechnologyAlexander Pastsyak, Rebrova Yana LQN – Model Example server users [0] workstation [5] net_2 [0.001] net_1 [0.001] server_2 [22] server_1 [10] disk_1 [0.01] printer [100] users{4} Z=3 workstations {4}network {inf} server_1server_2 printer disk_2 disk_1 disk_2 [0.01] disk_ 2

9. Page 9 SEC(R) 2008 © Siemens AG, Corporate TechnologyAlexander Pastsyak, Rebrova Yana Formalisms: Layered Queuing Networks AdvantagesDisadvantages Models are not suitable for formal verification LQN is the most powerful formalism to describe client- server systems Packages for direct solution and simulation are available Lack of good model editor with graphical user interface

10. Page 10 SEC(R) 2008 © Siemens AG, Corporate TechnologyAlexander Pastsyak, Rebrova Yana Formalisms: Queuing Petri Nets Generalized Colored Petri Net Queuing Petri Net T_EnterT_Service Tokens Places Immediate transitionTimed transition depositoryqueue

11. Page 11 SEC(R) 2008 © Siemens AG, Corporate TechnologyAlexander Pastsyak, Rebrova Yana QPN- Model Building Blocks Tokens are the “value” or “state” of a place Transitions Places Ordinary placesQueuing places Timed Transitions Immediate Transitions Tokens Tokens are inserted into the queue. After completion of its service, a token is immediately moved to the depository, where it becomes available for output transitions of the place. Tokens fired onto such a place are immediately available for the corresponding output transitions Immediate transition fires without any delay in zero time. An enabled timed transition fires after a certain delay. Transitions change the number of tokens in places

12. Page 12 SEC(R) 2008 © Siemens AG, Corporate TechnologyAlexander Pastsyak, Rebrova Yana QPN – Model Example Ordinary place Queuing place Immediate transition Clients Web Server 1DB Server DB connections pool

13. Page 13 SEC(R) 2008 © Siemens AG, Corporate TechnologyAlexander Pastsyak, Rebrova Yana Formalisms: Queuing Petri Nets AdvantagesDisadvantages Easy to model distributed client- server systems Analysis suffers the state space explosion problem and this imposes a limit on the size of the models that are analyzable QPME tool offers convenient graphical user interface for models editing QPME tool is under development and some problems occur in the analysis package Difficult to model synchronous requests Only simulation technique is currently available in QPME tool Models are not suitable for formal verification Allows to handle several request types in the same model

14. Page 14 SEC(R) 2008 © Siemens AG, Corporate TechnologyAlexander Pastsyak, Rebrova Yana Formalisms: Performance Evaluation Process Algebra Stochastic Process Algebra Performance Evaluation Process Algebra Duration is exponentially distributed Activity is called shared if several components synchronize over it The rate of the shared activity is defined by cooperation with another component. Process P1Process P2 a,r

15. Page 15 SEC(R) 2008 © Siemens AG, Corporate TechnologyAlexander Pastsyak, Rebrova Yana PEPA – Model Building Blocks Components carry out activities Activity Combinators Components Combinators allow building expressions to define behavior of components via activities. Each activity is characterized by an action type α and duration r which is exponentially distributed. This is written as a pair (α, r). CombinatorsSemantic Prefix(α, r).P ChoiceP1+P2 CooperationP1 P2 HidingP/L ConstantA def = P

16. Page 16 SEC(R) 2008 © Siemens AG, Corporate TechnologyAlexander Pastsyak, Rebrova Yana Component PEPA – Model Example ClientWeb ServerDatabase Internal structure of component a,r a1,r1 a2,r2 a5,r5 a3,r3 a4,r4 Cooperation

17. Page 17 SEC(R) 2008 © Siemens AG, Corporate TechnologyAlexander Pastsyak, Rebrova Yana Formalisms: Performance Evaluation Process Algebra AdvantagesDisadvantages Easy to model several synchronous components Analysis suffers the state space explosion problem and this imposes a limit on the size of the models that are analyzable PEPA Workbench supports only text models Some components (like Load Balancer) are not easy to model. Powerful tools for models analysis Models are suitable for formal verification Packages for direct solution and simulation are available It’s not easy to make graphical representation of the model

18. Page 18 SEC(R) 2008 © Siemens AG, Corporate TechnologyAlexander Pastsyak, Rebrova Yana Architecture of the Test System TitleHardwareSoftware Web Load Balancer 2.16Ghz Core2Duo PC Apache Web Server v2.2 with enabled modules mod_proxy and mod_proxy_balancer Web Server 1 3.5Ghz Celeron PC Apache Web Server v2.2 with enabled module mod_fast_cgi, PHP v5.2.6 compiled with fast_cgi support; CMS Joomla, v1.5.3 Web Server 2 2.2 Ghz Core2Duo PC DB Server 2.2 Ghz Core2Duo PC MySQL v 5.1

19. Page 19 SEC(R) 2008 © Siemens AG, Corporate TechnologyAlexander Pastsyak, Rebrova Yana Modeling of the test system - LQN Clients Load Balancer Database WebServer1WebServer2 Request processing [256] users [40] Request processing [8] Request processing [8] Request processing [inf] Workstation with Users Web Server 1 Web Server 2 DB Server 2 Load Balancer

20. Page 20 SEC(R) 2008 © Siemens AG, Corporate TechnologyAlexander Pastsyak, Rebrova Yana Modeling of the test system - QPN Clients Load Balancer Database WebServer1WebServer2 =? Thread pool

21. Page 21 SEC(R) 2008 © Siemens AG, Corporate TechnologyAlexander Pastsyak, Rebrova Yana Modeling of the test system - PEPA Clients Database WebServer1WebServer2 Load Balancer =? Component Cooperation

22. Page 22 SEC(R) 2008 © Siemens AG, Corporate TechnologyAlexander Pastsyak, Rebrova Yana Experiments Configuration 1 - LB Configuration 2 – PC1 Configuration 3 – PC2 Load Balancer WebServer1, WebServer2 Database WebServer1 Database WebServer2 Database Throughput and Response Time are measured for three different configurations with virtual users changing from 1 to 40

23. Page 23 SEC(R) 2008 © Siemens AG, Corporate TechnologyAlexander Pastsyak, Rebrova Yana Models Calibration Service rates for Web Server1,Web Server2, DB server = ? WebServer 2 (2.2 Ghz Core2Duo) 1 User RT = 0.6sec UsageCPU = 35% WebServer 2 Tprocessor = RT*UsageCPU*Ncores= =0.6*0.35*2 = 0.42 sec WebServer 1 (3.5Ghz Celeron) Tprocessor = 0.42/3.5*2.2 = 0.264 sec Rate WS1 = 0.42 -1 =2.38 sec -1 Rate WS2 = 0.26 -1 =3.78 sec -1 Rate DB = (0.6-0.42) -1 =5.5 sec -1 Need to define parameters in the models Experiment with one webserver and special workload – 1 user. Get the time spent by CPU for request processing Identify the same time for another webserver by normalization to CPU frequency

24. Page 24 SEC(R) 2008 © Siemens AG, Corporate TechnologyAlexander Pastsyak, Rebrova Yana Results: Throughput

25. Page 25 SEC(R) 2008 © Siemens AG, Corporate TechnologyAlexander Pastsyak, Rebrova Yana Results: Response Time

26. Page 26 SEC(R) 2008 © Siemens AG, Corporate TechnologyAlexander Pastsyak, Rebrova Yana Results: Model errors QPME model vs. experiment LQNS model vs. experiment PEPA model vs. experiment PC15.8%5.3%6.4% PC214.2%15.3%17.3% LB32.8%27.2%27.9% QPME model vs. experiment LQNS model vs. experiment PEPA model vs. experiment PC15.2%6.4%4.1% PC210.4%10.3%10.5% LB8.6% 8.5%

27. Page 27 SEC(R) 2008 © Siemens AG, Corporate TechnologyAlexander Pastsyak, Rebrova Yana Conclusions All of the applied techniques are able to predict system behavior without detailed knowledge about the internal system structure Difference between model predictions and experimental results lies in the acceptable area: for throughput it’s less than 10%,for response time – less than 30% Such results make possible to use model predictions during early performance analysis of infrastructure for distributed business applications The investigation of errors caused by hidden structure of system components and methods to estimate them is the subject for further work

28. Page 28 SEC(R) 2008 © Siemens AG, Corporate TechnologyAlexander Pastsyak, Rebrova Yana Q&A Thank you for attention!