A Low-cost and Scalable Visualization System for Electricity Consumption


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AIST booth presentation slides at SC2011.

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A Low-cost and Scalable Visualization System for Electricity Consumption

  1. 1. A Low-cost and Scalable Visualization System for Electricity Consumption Ryousei Takano Information Technology Research Institute,National Institute of Advanced Industrial Science and Technology (AIST), Japan SC2011@Seattle, Nov. 17 2011
  2. 2. Outline •  Background•  System overview•  Demonstration at SC11•  Summary 2
  3. 3. Background •  The power consumption of data centers and networks becomes an issue of vital importance to IT industries. Google data center in the Dalles, Oregon •  In Japan, we faced planed power outages (rolling power outages) due to power shortages caused by 3.11. Fukushima Daiichi Nuclear Power Plant 3
  4. 4. Motivation •  To plan electricity savings, visualization of electricity consumption per segmented unit, such as a power distribution board, is becoming essential.•  But, the total system cost and scalability are problem. –  a lot of distributed sensors...•  The system has to be low-cost, scalable, and ease to develop applications.   Cheap power measuring hardware unit   Power logging software utilizing cloud computing   A simple REST protocol 4
  5. 5. System overview Data collecting unit Data collecting unit 2 Data collecting unit … … 3 Data collecting server Update power usage Google App Engine using REST w/ JSON Retrieve data using Datastore REST w/ JSON Alert 4 Applications Viewer 1 Data measuring unit Observe the state of power consumption Plan electricity saving 5
  6. 6. Small start Go big Google App Engine Datastore 4 sensors 32 ports = 128 sensors Datastore Sensors can be incrementally installed, GAE can scale up according to the workload. ... 6
  7. 7. Low-cost power measuring unit •  Send data to data collecting unit every second. •  The production cost is approximately 120 USD, including the cost of 4 current sensors.Clamp-on current sensor (max: 4) RJ-45 port Signal processing board (dsPIC30F3013) 7
  8. 8. Data collecting unit (1/2) •  Gather data from up to 32 power measuring unit•  Push data to GAE –  Can be placed behind NAT To power measuring unit To GAE via the Internet (Not Ethernet, data transfer and power supply) (Ethernet/100BaseT) 8
  9. 9. Data collecting unit (2/2) Power GAE measuring unit RJ-45 ports x 32 CPU (SH3) board- Linux + Python Serial-Parallel signal transform (Now, it has been replaced by FPGA.) 9
  10. 10. Google App Engine •  PaaS cloud service for web applications –  Java, Python, Go are supported –  Your application will have URL like http://XXXX.appspot.com•  Scalable and stable data storage –  Data are replicated to 5 different datacenters –  Allows 2 of them to be lost during operation•  Maintenance free –  No need to manage, almost•  Almost free, for now –  Price change is scheduled this Dec. though. 10
  11. 11. REST API path method description /update POST Upload data /latest GET Get all data for the last minute /latest,N GET Get all data for the last N minutes /summary.s/YYYYmmDDHHMMSS,N GET Get all data for each second start from YYYYmmDDHHMMSS, for N seconds /summary.m/YYYYmmDDHHMM,N GET Get all data for each minute start from YYYYmmDDHHMM, for N minutes /summary.h/YYYYmmDDHH,N GET Get all data for each hour start from YYYYmmDDHH, for N hours /summary.d/YYYYmmDD,N GET Get all data for each day start from YYYYmmDD, for N days /query.s/LOC/YYYYmmDDHHMMSS,N GET Get data for locations that name start with LOC /query.m/LOC/YYYYmmDDHHMM,N GET /unit-config/UNIT_ID GET Get configuration data /unit-config/UNIT_ID PUT Set configuration data 11
  12. 12. Update from Data collecting unit Each data collection unit sends GAE xxx.appspot.com/update data every 20 seconds –  POST the following JSON string { "id": "UNIT_ID" "time": "1319837460” /* elapsed seconds from the UNIX epoch time */ "power": { /* data for the last 20 seconds per measurement point */ "sensor0.0": [VAL0, VAL1, VAL2, VA3, ..., VAL19], "sensor0.1": [VAL0, VAL1, VAL2, VA3, ..., VAL19], "sensor1.0": [VAL0, VAL1, VAL2, VA3, ..., VAL19], .... } } 12
  13. 13. Data retrieval Applications periodically (e.g., 1 GAE xxx.appspot.com/latest,N min) get data from GAE –  GET the following JSON string { "time": “1319837460” /* epoch time */ "timeStr": “201110290631” /* human readabletime in JST */ "power": { "LOCATION0": [1234] "LOCATION1": [1234] "LOCATION2": [1234] "LOCATION3": [1234] "LOCATION4": [1234] ... Viewer application }} 13
  14. 14. Demonstration at SC11 AIST (JP) 7 data collecting units Data collecting 82 sensor modules 1 gather unit Data collecting 290 measurement points unit 2 tore 1 … 3 view Sensor module … Clamp-on current transformer 2 Google App Engine Update power usage using REST w/ JSON Retrieve data using Datastore REST w/ JSON NICT booth #4717(US) 2 3 Data collection Viewer unit 1 Viewer 2 sensor built-in power strips AIST booth #917(US) 14
  15. 15. AIST server room (Japan) Data collecting unit in free access floor Clamp-on current sensor GAE Power distribution board Power measuring unit 15
  16. 16. NICT booth #4717 (US) 2 sensor modules (sensor built-in power strip) Tiled display wall server Data collecting module Juniper’s routers GAE 16
  17. 17. Visualization App. AIST server room (ACS cluster) at Japan NICT booth at the US 17
  18. 18. Summary •  Our newly developed system helps reduce total system cost and improve scalability by employing low-cost power measuring units (30 USD per measurement point), and utilizing cloud computing. –  The development of the system was completed within 3 months. –  At SC11, we have successfully demonstrated visualization of power data gathering from sensors installed at the US and Japan.•  Future work: Incorporate into reactive/dynamic server consolidation on a data center to reduce power consumption aggressively. 18
  19. 19. Q&A Thanks for your attention! Thank NICT members for their help in the demonstration.""This research was partially supported by the NEDO researchproject entitled “Research and Development Project for GreenNetwork/System Technology (Green IT Project).”" 19
  20. 20. Demo: GAE dashboard 0.75 HTTP requests/second 5000 bytes received/second 20
  21. 21. Visualization Applications less than 90% of the upper limit less than 95% of the upper limit more than 95% of the upper limit Offline (a) Web application (b) Desktop application 21
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