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Carnegie Mellon School of Computer Science Forecasting with Cyber-physical Interactions in Data Centers Lei Li PDL Seminar 9/28/2011.

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Presentation on theme: "Carnegie Mellon School of Computer Science Forecasting with Cyber-physical Interactions in Data Centers Lei Li PDL Seminar 9/28/2011."— Presentation transcript:

1 Carnegie Mellon School of Computer Science Forecasting with Cyber-physical Interactions in Data Centers Lei Li leili@cs.cmu.edu PDL Seminar 9/28/2011

2 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 2(c) Lei Li 2012

3 What is co-evolving time series? 3 Correlated multidimensional time sequences with joint temporal dynamics (c) Lei Li 2012

4 Goal: generate natural human motion –Game ($57B) –Movie industry Challenge: –Missing values –“naturalness” 4 Motion Capture Right hand Left hand walking motion [Li et al 2008a] (c) Lei Li 2012

5 Environmental Monitoring Problem: early detection of leakage & pollution Challenge: noise & large data 5 Chlorine level in drinking water systems [Li et al 2009] (c) Lei Li 2012

6 Network Security Challenge: Anomaly detection in computer network & online activity 6 BGP # updates on backbone from http://datapository.net/ Webclick for news from NTT Webclick for TV (c) Lei Li 2012

7 Time Series Mining Problems Forecasting Imputation (missing values) Compression Segmentation, change/anomaly detection Clustering Similarity queries Scalable/Parallel/Distributed algorithms 7 See my thesis for algorithms covering these problems (c) Lei Li 2012

8 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 8(c) Lei Li 2012

9 Datacenter Monitoring & Management Temperature in datacenter Goal: save energy in data centers –US alone, $7.4B power consumption (2011) Challenge: –Huge data (1TB per day) –Complex cyber physical systems 9(c) Lei Li 2012

10 Typical Data Center Energy Consumption LBL data center Google data center [Barroso 09] [LBNL/PUB-945] 10(c) Lei Li 2012

11 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? 11 JHU data center with Genomote (c) Lei Li 2012

12 Air cycle in DC 12(c) Lei Li 2012


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