Download Time Series Clustering: Complex is Simpler!

Carnegie Mellon
School of Computer Science
Forecasting with Cyber-physical
Interactions in Data Centers
Lei Li
[email protected]
9/28/2011
PDL Seminar
Outline
• Overview of time series mining
– Time series examples
– What problems do we solve
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Motivation
Experimental setup
ThermoCast: the forecasting model
Results
Other time series models and algorithms
(c) Lei Li 2012
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What is co-evolving time series?
Correlated multidimensional time
sequences with joint temporal dynamics
(c) Lei Li 2012
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[Li et al 2008a]
Motion Capture
• Goal: generate natural human
motion
– Game ($57B)
– Movie industry
• Challenge:
– Missing values
– “naturalness”
Right hand
walking motion
Left hand
(c) Lei Li 2012
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Environmental Monitoring
• Problem: early detection of leakage & pollution
• Challenge: noise & large data
Chlorine level in drinking water
systems [Li et al 2009]
(c) Lei Li 2012
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Network Security
• Challenge: Anomaly detection in computer
network & online activity
BGP # updates on backbone
from http://datapository.net/
Webclick for news
from NTT
Webclick for TV
(c) Lei Li 2012
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Time Series Mining Problems
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Forecasting
Imputation (missing values)
Compression
Segmentation, change/anomaly detection
Clustering
Similarity queries
Scalable/Parallel/Distributed algorithms
See my thesis for algorithms covering these problems
(c) Lei Li 2012
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Outline
• Overview of time series mining
– Time series examples
– What problems do we solve
•
•
•
•
•
Motivation
Experimental setup
ThermoCast: the forecasting model
Results
Other time series models and algorithms
(c) Lei Li 2012
8
Datacenter Monitoring & Management
• Goal: save energy in data
centers
– US alone, $7.4B power
consumption (2011)
• Challenge:
– Huge data (1TB per day)
– Complex cyber physical
systems
(c) Lei Li 2012
Temperature in datacenter
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Typical Data Center Energy Consumption
• LBL data center
electric
room
air 3%
movement
8%
lighting
4%
UPS
losses
8%
Cooling
tower
3%
• Google data center
DC
equipment
3%
Server
46%
CRAC
25%
[LBNL/PUB-945]
[Barroso 09]
(c) Lei Li 2012
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Towards Thermal Aware DC Management
• Data centers are often over provisioned, with
≈40% of energy spent for cooling (total=$7.4B)
• How can we improve energy efficiency in
modern multi-MegaWatt data centers?
JHU data center
with Genomote
(c) Lei Li 2012
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Air cycle in DC
(c) Lei Li 2012
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