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A Scalable and Distributed Electrical Power Monitoring System Utilizing Cloud Computing
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A Scalable and Distributed Electrical Power Monitoring System Utilizing Cloud Computing


CUTE 2013

CUTE 2013

Published in Technology , Business
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  • 1. A  Scalable  and  Distributed     Electrical  Power  Monitoring  System    U:lizing  Cloud  Compu:ng   Ryousei  Takano,  Hidemoto  Nakada,   Toshiyuki  Shimizu,  Tomohiro  Kudoh     Informa(on  Technology  Research  Ins(tute,     Na(onal  Ins(tute  of  Advanced  Industrial  Science  and  Technology  (AIST),  Japan   CUTE2013@Da  Nang,  Vietnam,  Dec.  19  2013  
  • 2. Outline   •  Background   •  System  overview   •  Design  of  hardware  and  soKware   •  Deployment  at  AIST  campus   •  Summary   2  
  • 3. Background   •  The  power  consumpPon  of  data   centers  and  networks  becomes   an  issue  of  vital  importance  to     IT  industries.   Google  data  center  in  the  Dalles,  Oregon       •  In  Japan,  there  is  an  urgent   need  for  green  IT  technologies   aKer  March  11th,  2011.   Fukushima  Daiichi  Nuclear  Power  Plant   3  
  • 4. Mo:va:on   •  VisualizaPon  is  key  to  plan  power  savings.   •  The  total  system  cost  and  scalability  are  problem.   –  Our  server  room  has  over  100  racks.   –  Our  campus  are  geographically  distributed  in  Japan.   •  The  system  has  to  be  low-­‐cost,  scalable,  and  also  ease   to  develop  applicaPons.   ➡ Cheap  power  monitoring  hardware   ➡ Power  monitoring  soKware  uPlizing  cloud  compuPng   ➡ A  simple  REST  API   4  
  • 5. System  overview   Data collecting unit Data collecting unit 2 Data collecting unit … … Update power usage using REST w/ JSON 3 Data store Google App Engine Data store Retrieve data using REST w/ JSON Alert 4 Applications 1 Power measuring unit Viewer Observe the state of power consumption Plan power saving 5  
  • 6. Small  start  Go  big   Google  App  Engine   Data  store   4  sensors   32  ports   =  128  sensors   Data  store   Sensors  can  be  incrementally  installed.   ...   6  
  • 7. Low-­‐cost  power  measuring  unit     •  Send  data  to  data  collecPng  unit  every  second.   •  The  producPon  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. Data  collec:ng  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   (Not  Ethernet,  data  transfer  and  power  supply)   To  GAE  via  the  Internet   (Ethernet/100BaseT)   8  
  • 9. Data  collec:ng  unit  (2/2)   Power Measuring Unit data store RJ-45 ports x 32 CPU board (T-SH7706LSR) -  SH3 Linux -  Buildroot 2011.05 - Serial/Parallel converter (Xilinx Spartan-3E) 9  
  • 10. Data  store  and  REST  protocol   data store config DB Configuration power logging DB Data collecting unit “unit” Get, query Update Application Power measuring unit “sensor” Current sensor “probe” Application … … 10  
  • 11. Google  App  Engine   •  PaaS  cloud  service  for  web  applicaPons   –  Java,  Python,  and  Go  are  supported   –  Your  applicaPon  will  have  URL  like     hgp://   •  Scalable  and  stable  data  storage   –  Data  are  replicated  to  5  different  datacenters   –  Allows  2  of  them  to  be  lost  during  operaPon   •  Maintenance  free   –  No  need  to  manage,  almost   •  Cost  effecPve   –  Almost  free  of  charge   11  
  • 12. REST  API   path   method   descrip:on   /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  locaPons  that  name  start  with  LOC   /query.m/LOC/YYYYmmDDHHMM,N   GET   /unit-­‐config/UNIT_ID   GET   Get  configuraPon  data   /unit-­‐config/UNIT_ID   PUT   Set  configuraPon  data   12  
  • 13. Update  from  Data  collec:ng  unit   Each  data  collecPon  unit  sends   data  every  20  seconds   GAE   –  POST  the  following  JSON  string   {            "id":      "UNIT_ID"            "Pme":  "1319837460”    /*  elapsed  seconds  from  the  UNIX  epoch  Pme  */            "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],                  ....            }   }   13  
  • 14. Data  retrieval   An  applicaPon  periodically  (e.g.,  1   min)  gets  data  from  GAE   GAE,N   –  GET  the  following  JSON  string   {          "Pme":  “1319837460”  /*  epoch  Pme  */          "PmeStr":  “201110290631”  /*  human  readable   Pme  in  JST  */          "power":  {                  "LOCATION0":  [1234]                  "LOCATION1":  [1234]                  "LOCATION2":  [1234]                  "LOCATION3":  [1234]                  "LOCATION4":  [1234]                  ...          }   }   Viewer  applicaPon   14  
  • 15. Deployment  at  AIST  campus   Server  room   10  data  collecPng  units   177  power  measuring  units   620  measurement  points   Data  collecPng   unit   Data  collecPng   unit   1 1 2 …   Sensor  module   Clamp-­‐on   current  transformer   Update  power  usage   using  REST  w/  JSON     2 store   3 …   gather   view   Google  App  Engine   Retrieve  data  using   REST  w/  JSON   Datastore   Clean  room   1 Data  collecPon   unit   2 3 billing  service   Viewer   15  
  • 16. Installa:on  in  AIST  server  room   Data collecting unit in free access floor Clamp-on current sensor Power distribution board data store Power measuring unit 16  
  • 17. Summary   •  Our  proposed  system  helps  reduce  total  system  cost  and   improve  scalability  by  employing  low-­‐cost  power  measuring   units  (30  USD  per  measurement  point),  and  uPlizing  cloud   compuPng.   –  The  development  of  the  system  was  completed  within  3  months.   –  We  have  successfully  operated  it  over  2  years  for  to  provide  an   electricity  billing  service  and  evaluate  the  power  efficiency  of  data   processing  middleware.   •  Future  work   –  Tolerance  for  network  failures.   –  More  applicaPons:  e.g.,  server  consolidaPon  on  a  private  cloud  to   reduce  power  consumpPon.   17  
  • 18. Q&A   Thanks  for  your  agenPon!   This  research  was  parPally  supported  by  the  NEDO  research  project   enPtled  “Research  and  Development  Project  for  Green  Network/ System  Technology  (Green  IT  Project).”   18  
  • 19. Visualiza:on  Applica:ons   less  than  90%  of  the  upper  limit   less  than  95%  of  the  upper  limit   more  than  95%  of  the  upper  limit   Offline   (a)  Web  applicaPon   (b)  Desktop  applicaPon   19