Transcript Mechanisms for Quality of Service in Web Clusters
Terena Networking Conference - TNC2001
Mechanisms for Quality of Service in Web Clusters
V. Cardellini, E. Casalicchio, S.Tucci
University of Roma “Tor Vergata”
M. Colajanni
University of Modena Speaker:
Emiliano Casalicchio [email protected]
http://www.ce.uniroma2.it/people/casali
Additional Info: www.ce.uniroma2.it
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 May 2001 Terena Networking Conference TNC2001 2
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 May 2001 Terena Networking Conference TNC2001 3
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 May 2001 Terena Networking Conference TNC2001 4
Quality of Web Services (QoWS)
High performance systems Systems for Quality of Service • 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
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From QoS to QoWS in Web clusters
• 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
Our idea: starting from main QoS principles
– classification – performance isolation – high resource utilization – request admission control
QoWS
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• •
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) May 2001 Terena Networking Conference TNC2001 7
A QoWS-enabled Web cluster architecture
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QoS-blind dispatching algorithms
• Round-Robin (RR) • Least-Loaded server (LL) • Weighted Round-Robin (WRR) • Server Admission with priority (SerADM-SerPRI) May 2001 Terena Networking Conference TNC2001 9
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
)
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2 May 2001 Terena Networking Conference TNC2001 10
QoS-aware algorithms
SerADM-SerPRI SwiADM SwiADM-SerPRI Partition Classification Perf.Isolation High Res.Util. Req.Adm
Yes Yes Yes Yes Yes No Yes Yes No No No Yes Yes Yes Yes Yes May 2001 Terena Networking Conference TNC2001 11
System and workload model
Parameter Value (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 ( Pareto ( = 1.4, Lognormal (
k
= 2) = 1.33,
k
= 1) = 7.640, Pareto ( = 1.383,
k
= 1.705 ) = 2924)
Service Classes High (30%) - Medium (26.5%) - Low (43.5%)
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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 May 2001 Terena Networking Conference TNC2001 13
Simulation results (1)
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Simulation results (2)
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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 May 2001 Terena Networking Conference TNC2001 16
Work in progress
• Level-7 Web switch with QoS-enabled policies • New policies for dynamic request partitioning • Prototype implementation May 2001 Additional information: www.ce.uniroma2.it
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