A Robot as Mobile Sensor and Agent in Data Center Energy Management

Transcription

1 A Robot as Mobile Sensor and Agent in Data Center Energy Management Hoi Chan*, Jonathan Connell*, Canturk Isci*, Jeffrey O. Kephart*, Jonathan Lenchner*, Chris Mansley and Suzanne McIntosh* * IBM T.J. Watson Research Center, Hawthorne, NY Department of Computer Science, Rutgers University, Piscataway, NJ ICAC 2011: June 14-18, Karlsruhe, Germany

2 Outline Robot Overview What is the Data Center Robot? What can the robot do and why is it important? Robot Design / High Level Architecture Integration into Commercial Software (IBM s Maximo for Energy Optimization or MEO) Pre-robot Days Robot as Mobile Sensor Robot as Agent Under Human Control As Autonomous Agent 2 ICAC 2011: June 14-18, Karlsruhe, Germany

3 Robot Overview 2-meter pole arrayed with sensors Webcam Netbook Roomba base Autonomously collects data center layout and sensor data Obviates laborious manual collection Output format can be read by Maximo for Energy Optimization No prior knowledge of data center needed: just set it down and turn it on Uses square tile grid for navigation Full data center coverage Robustly avoids obstacles and copes with collisions Low construction cost Provides key support for analytics Data are used to generate physics and asset models on which diagnostic and predictive analytics rely If left in residence, robot further supports analytics via fine-grained periodic sensing and on-demand remote viewing of trouble spots Obviates large up-front costs of installing fixed environmental sensors Practically any sensor can be mounted on the robot (provided not too heavy) Regular tiles Perforated tiles Racks or other obstacles Asset layout and temperature map collected by robot at IBM Poughkeepsie Green Data Center 3 ICAC 2011: June 14-18, Karlsruhe, Germany

4 Why Map out a Data Center and Provide a Thermal Profile? Very time consuming to specify asset locations by hand, or even to move asset data from one system to another. Often asset tracking systems, relying on manual input, are out of date Data center layouts and thermal maps can be used as input to Tivoli s Maximo Asset Management for Energy Optimization (MEO) which has various tools to help optimize cooling Data Center cooling is very expensive! ~$300M/year to cool IBM s data centers worldwide After thorough mapping and thermal profiling of the data center is done, still need ongoing monitoring Data center layouts change and workloads vary Initial dense scan should inform subsequent, more time-constrained scans 4 ICAC 2011: June 14-18, Karlsruhe, Germany

5 Robot High Level Design / Architecture 5 ICAC 2011: June 14-18, Karlsruhe, Germany

6 Integration into IBM s Maximo Asset Management for Energy Optimization (MEO) What is MEO? First of all an asset management system manages the lifecycle of IT and non-it assets in all kinds of facilities, not just data centers: List of assets in a data center on our test system (first 20 if 2810 total assets shown) 6 ICAC 2011: June 14-18, Karlsruhe, Germany

7 Integration into IBM s Maximo Asset Management for Energy Optimization (MEO) What is MEO? Drilling down to see asset details in MEO 7 ICAC 2011: June 14-18, Karlsruhe, Germany

8 Integration into IBM s Maximo Asset Management for Energy Optimization (MEO) What is MEO? Provides various tools for optimizing energy efficiency in data centers MEO Heat Map 8 ICAC 2011: June 14-18, Karlsruhe, Germany

9 Integration into IBM s Maximo Asset Management for Energy Optimization (MEO) Pre-robot: Needed static sensors or a human pushing a mobile sensing station to populate MEO with data to make these energy optimization tools useful: Pre-robot: the mobile sensing station, a.k.a. the cart 9 ICAC 2011: June 14-18, Karlsruhe, Germany

10 Integration into IBM s Maximo Asset Management for Energy Optimization (MEO) With the advent of the robot: MEO Robot 10 ICAC 2011: June 14-18, Karlsruhe, Germany

11 Robot as Agent (under Human control) User viewing a (perforated) tile image taken by the robot O indicates robot starting location, X where the robot is now 11 ICAC 2011: June 14-18, Karlsruhe, Germany

12 Robot as Agent (under Human control) After some racks have been moved, a user marks a tile or entire neighborhood as unknown forcing the robot to remap the given region. 12 ICAC 2011: June 14-18, Karlsruhe, Germany

13 Robot as Autonomous Agent MEO can automatically diagnose hot spots and cold spots in data centers Automatically dispatch robot to such an area Get finer grained sense of region of interest, instead of interpolating from a few fixed sensors i.e. to get a better sense of where the hot spot is coming from Take tile images, or images of effected racks. Conceivably a perforated tile is blocked or there is something blocking the air inlet area of servers Schedule the robot to make periodic scans You have a large data center and need a quick scan to determine if things are in reasonably good order thermally (and humidity-wise) Robot can determine most informative points to scan given a limited time budget to scan in 13 ICAC 2011: June 14-18, Karlsruhe, Germany

14 Robot Automatically Dispatched in Response to Developing Hot Spot Robot orients itself within the MEO map The hot/cold spot map pictured above differs from the more typical heat map by pointing out areas near the air inlets of racks (typically in cold aisles ) that exceed specific hot thresholds and other areas ( cold spots ) that exceed cold thresholds and are indicative of the wasteful use of cooling. Upon the detection of a hot (or cold) spot the robot is automatically dispatched to get a finer grained temperature distribution in so doing it also notices that a tile is blocked. 14 ICAC 2011: June 14-18, Karlsruhe, Germany