1. Mechanisms for Quality of Service in Web Clusters V. Cardellini, E. Casalicchio, S.Tucci M. Colajanni University of Roma “Tor Vergata” University of Modena Speaker: Emiliano Casalicchio ecasalicchio@ing.uniroma2.it http://www.ce.uniroma2.it/people/casali Speaker: Emiliano Casalicchio ecasalicchio@ing.uniroma2.it http://www.ce.uniroma2.it/people/casali Terena Networking Conference - TNC2001 Additional Info: www.ce.uniroma2.it

2. May 2001Terena Networking Conference - TNC2001 2 Outline Motivations –Quality of Service & Quality of Web Services System architecture QoS-blind vs. QoS-aware dispatching algorithms Results –System and workload model –Performance metrics –Simulation results Summary

3. May 2001Terena Networking Conference - TNC2001 3 Why QoS in Web services? The second generation of Web sites –communication channel for critical information –fundamental technology for information systems of the most advanced companies and organizations –business-oriented media The new Web requires –differentiation of users and services –supports to heterogeneous applications and user expectations –differentiated pricing for content hosting and service providing

4. May 2001Terena Networking Conference - TNC2001 4 A Web cluster architecture for high performance Web services IBM TCP Router CISCO Local Director IBM NetDispatcher Foundry Networks’ ServerIron family CISCO HP WebQoS Local Director

5. May 2001Terena Networking Conference - TNC2001 5 Quality of Web Services (QoWS) QoS principles and mechanisms have been deeply studied in the computer network area, but –QoS principles are not immediately applicable to the server side of the Web System –Network QoS and server QoWS principles must be combined to provide a peer-to-peer QoS for Web services The focus of this talk will be on QoWS for Web clusters High performance systems  Systems for Quality of Service

6. May 2001Terena Networking Conference - TNC2001 6 From QoS to QoWS in Web clusters Our idea: starting from main QoS principles –classification –performance isolation –high resource utilization –request admission control To define QoWS principles we need to find out –feasible mechanisms to achieve QoWS –Web Cluster components that can implement the QoWS principles and mechanisms QoWS

7. May 2001Terena Networking Conference - TNC2001 7 QoWS principles Classification (at layer-4/7 Web Switch) –clients and services classification –users identification Performance isolation –queuing scheduling policies (at Web server: CPU,disk,…) –resource partitioning (at the Web server for fine-grain level, at the Web Switch for coarse-grain level) High resource utilization (at Web switch/server) –dynamic resource partitioning Request admission (at Web switch/server) –estimation of resource need (at Web switch) –access control mechanism (at Web switch/server)

8. May 2001Terena Networking Conference - TNC2001 8 A QoWS-enabled Web cluster architecture

9. May 2001Terena Networking Conference - TNC2001 9 QoS-blind dispatching algorithms Round-Robin (RR) Least-Loaded server (LL) Weighted Round-Robin (WRR) Server Admission with priority (SerADM-SerPRI)

10. May 2001Terena Networking Conference - TNC2001 10 QoS-aware dispatching algorithms without partitioning of Web servers –Switch Admission (SwiADM) –Switch Admission with server priority (SwiADM-SerPRI) with partitioning of Web servers –Dynamic partition of servers (Partition)

11. May 2001Terena Networking Conference - TNC2001 11 QoS-aware algorithms SerADM-SerPRI SwiADM SwiADM-SerPRI Partition YesYesNoYes YesNoNoYes YesYesNoYes YesYesYesYes ClassificationPerf.IsolationHigh Res.Util.Req.Adm

12. May 2001Terena Networking Conference - TNC2001 12 System and workload model ParameterValue (default) Number of servers Disk parameter Memory transfer rate Intra-server bandwidth 10 20 MBps, 7200 RPM, 0.05 msec c.d., 9 msec s.t. 100 MBps 100 Mbps switched LAN Arrival rate Requests per session User think time Embedded objects Hit size - body Hit size - tail 100 - 500 clients per second (300cps) Inverse Gaussian (  = 3.86, = 9.46 ) Pareto (  = 1.4, k = 2) Pareto (  = 1.33, k = 1) Lognormal (  = 7.640,  = 1.705 ) Pareto (  = 1.383, k = 2924) Service ClassesHigh (30%) - Medium (26.5%) - Low (43.5%)

13. May 2001Terena Networking Conference - TNC2001 13 Performance metrics 90-percentile of page delay –measure the completion time of a Web page at the Web cluster side –the X-percentile is used to define the Service Level Agreement (SLA) for predictive services Percentage of dropped requests –measure the percentage of users that perceive a deny of service

14. May 2001Terena Networking Conference - TNC2001 14 Simulation results (1)

15. May 2001Terena Networking Conference - TNC2001 15 Simulation results (2)

16. May 2001Terena Networking Conference - TNC2001 16 Conclusions Basic requirements for QoWS are satisfied by policies that integrate main mechanisms for network-QoS into main components of a Web cluster (i.e., Web servers and/or Web switch): –priority scheduling –dynamic server partitioning –admission control

17. May 2001Terena Networking Conference - TNC2001 17 Work in progress Level-7 Web switch with QoS-enabled policies New policies for dynamic request partitioning Prototype implementation Additional information: www.ce.uniroma2.it