xs sho niboshi
TRANSCRIPT
Research Objective
Conventional Approach
Idea of Resource Control
Methodology
Experiment
Results
Conclusion
2
Proposes effective resource management method in a virtualized system under dynamic workload
What is a good resource manager?
Maintains application performance with minimal resources
Balances performance between applications
3
Conventional method allocates resources based on each VM’s demand:
4
Resource Allocation
Performance
Resource Allocation
Performance
Allocate resources based on relative performance
5
Mail Domain App Domain Mail Domain App Domain
Keeps the performance balanced!
Resource Resource
Pe
rfo
rma
nc
e
Pe
rfo
rma
nc
e
6
Mail server
QoS Controller
Mail Domain
DT LR
Arbitration Controller
Control Domain
App server
QoS Controller
App Domain
TT
Allocates CPU time
Req Req
①
②
③
⑤
④
QoS controller
Purpose: determine the amount of resources to maintain acceptable performance
Method: utilizes the empirical relationship between the performance and the allocated resources
modeled by Fuzzy control theory which incorporates the experience of a human process in its control design
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Arbitration Controller
Purposes : balances relative performance of domains
Method: adjusts to system capacity and builds resource capacity layout
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Example:Domain A, Domain B
Request: 60% + 90% = 150%Allocation:40% + 60% = 100%
Xen Summit AMD 2010 9
Cap-none
Cap-all
Resource Utilization
Resourc
e S
epara
tion
※Q1=QoS in domain1
Q2=QoS in domain2
Resource separation takes some overheads (unused resources)
Select most efficient capacity layout
Cap-some
Reqtotal < 100%
Q1 ≠ Q2
Q1 ≠ Q2
Q1 ≠ Q2
Reqtotal < 100%
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System Specification
CPU AMD Athlon x2 (Dual Core) 2.0 GHz
Main Memory 4GB
HDD SATA 7200rpm x2
OS CentOS 5.2 (kernel 2.6.18)
VirtualizationSoftware
Xen hypervisor 3.2.2
Domain QoS indicator Workload
Mail domain Delivery TimeLogin Rate
SPECmail2001
Java app domain Transaction Time SPECjbb2005
Control CPU time
Experiments with two workload scenarios
Compare
WRC (With Proposed Resource Manager)
Default (Default Scheduler in Xen)
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Intervals Scenario ↑Mail Scenario ↑Java
Sec Mail Java Mail Java
1-399 Medium Medium Medium Medium
400-1199 High Medium Medium High
1200-1600 Medium Medium Medium Medium
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0
10
20
30
40
50
Delivery Time (sec)
Default WRC
0
0.05
0.1
0.15
0.2
0.25
Transaction Time (msec)
Default WRC
Mail increase Mail increase
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0
1
2
3
4
5
6
Delivery Time (sec)
Default WRC
0
0.05
0.1
0.15
0.2
0.25
Transaction Time (msec)
Default WRC
Java increase Java increase
Resource Request follows QoS states
Adaptation delay occurs occasionally
In low priority domain, some requests don’t take account of QoS state Request is based on
current CPU consumption
Xen Summit AMD 2010 14
QoS Controller
Mail server
Arbitration Controller
App server
QoS Controller
0
10
20
30
40
50
60
0
0.05
0.1
0.15
0.2
0.25
0.3
0 200 400 600 800 1000 1200 1400 1600
% of total CPU (Request)
TransactionTime (msec)
Java - QoS vs. Request (↑Mail)
TransactionTime Request
0
10
20
30
40
50
60
70
80
0
10
20
30
40
50
60
0 200 400 600 800 1000 1200 1400 1600
% of total CPU (Request)
Delivery Time (sec)
Mail - QoS vs. Request (↑Mail)
DeliveryTime Request
The ratio between Consumption and Request is quite unstable
Different capacity layouts lead to different resource distributions
Xen Summit AMD 2010 15
QoS Controller
Mail server
Arbitration Controller
App server
QoS Controller
0.7
0.8
0.9
1
1.1
1.2
0.7 0.8 0.9 1 1.1 1.2Consumption / Request (Java)
Consumption / Request (Mail)
Consumption / Request Distribution
both Caps are 100
both caps are not 100
only Mail's Cap is 100
onlyJava's Cap is 100
0.8
0.9
1
1.1
1.2
0 500 1000 1500
ratio
Consumption / Request (↑Mail)
Ratio (Mail/Java)
• Proposed effective resource manager– Resource allocation reflecting application states
– Better performance than conventional method in one experiment
• However, worse performance in the other experiment
• Future work– Fast adaptation
– Uses variation of QoS state as control parameter– Dynamic rule construction
– Fair resource allocation– Needs more consideration about cap=100 (=0)
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