ieee 7th annual workshop on workload characterization the usar characterization model adriano...
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IEEE 7th Annual Workshop on Workload Characterization
The The USARUSARCharacterization ModelCharacterization Model
Adriano Pereira, Gustavo Gorgulho, Leonardo Silva, Wagner Meira Jr., and Walter Santos
{adrianoc,gorgulho,leosilva,meira,walter}@dcc.ufmg.br
Department of Computer ScienceFederal University of Minas Gerais (UFMG)
Belo Horizonte - Brazil
October, 2004
e-Commerce, Systems Performance Evaluation, and Experimental Development Laboratory
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Presentation IndexPresentation Index
• Introduction
• Goals
• Methodology– Characterization Model– Validation Model
• Case Study
• Conclusion and Ongoing Work
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IntroductionIntroduction
• Understanding the nature and characteristics of Web workloads is a crucial step to improve the quality of the offered service– Design systems with better Performance and
Scalability.
• Workload Characterization Methodologies and Techniques– Guidelines to characterize and generate workloads
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IntroductionIntroduction
• Workload Characterizations typically do not consider reactivity aspects– Do not consider agreggate information from user
and server-side– Generate the same workload despite the server
response time
ServerClientRequest
Response
e-Commerce, Systems Performance Evaluation, and Experimental Development Laboratory
e-speedGoalsGoals
• Characterize and replicate the behavior related to user reactivity
• Analyze and model the way users react to variations in the quality of service provided.– Correlate user and server-side
• Validate the model through simulation.
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MethodologyMethodology
• When we look at the interaction process we have sequences of requests and responses– IAT (inter-arrival time): time between requests
• User-side related measure
– Latency: time to process and answer the request• Server-side related measure
LATENCY
IAT
Server
Client
REQUEST
RESPONSE
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MethodologyMethodology
• The USAR Characterization Model– Conceptual views
USER (U)USER (U)
SESSION (S)SESSION (S)
ACTION (A)ACTION (A)
REQUEST (R)REQUEST (R)
• User: user behavior considering quality of service
• Session: actions between a threshold τ
• Action: clicks from the user
• Requests: objects associated with a action
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User Level CharacterizationUser Level Characterization
1) Prepare log: generate a temporary log Lu by aggregating the sessions per user;
2) Analyze users from the following perspectives:– IAT and Latency ratio;– IAT and Latency difference;
3) Discretize IAT and Latency measures using a correlation function;
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User Level Characterization -User Level Characterization - Discretization ModelDiscretization Model
• 7 User Classes (A – G)
DIFDIF
k5k5
k6k6
RATRAT
CC
BB
AA
EE
FF
GG
DD
00 k1k1k2k2
k3k3
k4k4
PatiencePatienceImpatienceImpatience
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User Level CharacterizationUser Level Characterization
4) Transform user sessions into sequences of user classes according to discretization criteria from item 3);– Ex: A A B F B G G G G A
5) Evaluate the sequences in order to group them using similarity; – Sequence mining (SPADE tool) or
matching
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User Level CharacterizationUser Level Characterization
• Classify them in User Profiles:
–Patient
k5k5
k6k6
RATRAT
CC
BB
AA
EE
FF
GG
DD
00 k1k1k2k2
k3k3
k4k4
–Impatient
–Impatient Tendency–Continuous
–Patient Tendency–Inconstant
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User Level CharacterizationUser Level Characterization
6) Process the log Lu applying a function f(Lu), which maps sequence of classes to groups defined in step 5;
7) Apply Clustering;
8) Analyze the clusters and classify them.
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MethodologyMethodology
• Validation using the USAR Simulation Model
USAR
Inputs
• Users Types• Behaviors and Profiles• Session Length Dist.• Action Popularity• Object Size• Object Popularity
Parameters• # User Sessions
Log of User Reactions per Session
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Case StudyCase Study
• Proxy-cache of Federal University of Minas Gerais (UFMG);
• 4 weeks of logs.
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Case StudyCase Study
• Distribution of Sessions and User Profiles
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Case StudyCase Study
• Validation through simulationUSAR
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ConclusionConclusion
• We propose the USAR characterization methodology that comprehend the levels of request, action, session and user– Generic Methodology applicable to any workload
• Model reactivity aspects using inter-arrival time and latency that has been interesting and promising– Present a discretization model based on the radio
and difference between IAT and latency
• Validate the model through simulation