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

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CUTE 2013

CUTE 2013

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

  • 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 -  pmon.py 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 pmon.py pmon.py pmon.py 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://XXXX.appspot.com   •  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   xxx.appspot.com/update   –  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   xxx.appspot.com/latest,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