DOI QR코드

DOI QR Code

Potential Roles of Awareness Computing Technology for Energy Management

에너지 관리를 위한 인식 컴퓨팅의 잠재적 역할 연구

  • Received : 2011.05.22
  • Accepted : 2011.06.04
  • Published : 2011.06.30

Abstract

Energy management aims to financial and ecological success by optimizing the energy consuming sources such as sensors, computers and appliances. Hence, acquiring energy-related data from the sources in an automated manner is the starting point of managing energy. Recently, awareness computing has been emerging in system and cybernetics area. Awareness is the most fundamental ability for any living things to survive, and also the first step to make systems intelligent with the help of artificial intelligence. Even though the potential reciprocal benefits between energy management and awareness computing, frameworks which show how awareness computing contributes to manage energy-related strategy have been very few. Hence, this paper aims to introduce the awareness computing issues to improve energy management. In particular, we focus on satisfaction awareness computing which potentially realize the balance of energy savings and user's utility.

에너지 관리는 센서, 컴퓨터나 가전기기와 같은 원천들의 에너지 소비를 최적화함으로써 재정적 생태적 성공을 달성하는 것이 목적이다. 따라서 각 원천들로부터 에너지 측정과 관련된 자료들을 획득하는 것이 에너지 관리의 출발점이다. 최근 상황인식 컴퓨팅을 아우르는 다른 인식컴퓨팅이라는 분야가 정보기술 영역에서 새롭게 부각되고 있다. 인식이란 생물체들의 생존을 위한 가장 기본적인 능력임과 동시에 인공지능의 도움으로 정보 시스템을 지능화하는 시발점이 될 수 있다. 이렇게 에너지 관리와 인식 컴퓨팅 연구가 상호 호혜적인 이익을 획득할 것임에도 불구하고 인식 컴퓨팅이 어떻게 에너지 관련 전략에 기여할 것인지에 대한 연구는 거의 존재하지 않는다. 따라서 본 논문의 목적은 에너지 관리 개선을 위한 인식 컴퓨팅 연구 이슈에 대해서 소개하는 것이다. 특히 인식 컴퓨팅이 에너지 절감과 사용자의 효용간의 균형을 실현하는 역할에 대해 집중하였다.

Keywords

References

  1. Benini, L., A. Boglio and G. Michelli, "A survey of design techniques for system-level dynamic power management", IEEE Transactions on VLSI Systems, Vol.8, No.3(2000), 299-316.
  2. Bernard, T. and H. B. Kuntze, Sensor-Based Management of Energy and Thermal Comfort, In O. Gassmann and H. Meixner (eds), Sensors in Intelligent Buildings, Weinheim, Germany, Wiley-VCH. 2001.
  3. Kim, D., J. J. Garcia-Luna-Aceves, K. Obraczka, J. Cano and Manzoni, P. "Power-aware routing based on the energy drain rate for mobile ad hoc networks", Proceedings of the 11th Int'l Conf. Computer Comm. and Networks (ICCCN 2002), (2002), 565-569.
  4. Fanger, P. O., Thermal Comfort, New York, McGraw- Hill.
  5. Fryman, J. B., C. M. Huneycutt, H. S. Lee, K. M. Mackenzie and D. E. Schimmel, "Energyefficient network memory for ubiquitous devices", IEEE Micro, Vol.23, No.5(2003), 60-70. https://doi.org/10.1109/MM.2003.1240213
  6. Gamou, S., R. Yokoyama and K. Ito, "Optimal unit size of cogeneration systems in consideration of uncertain energy demands as continuous random variables", Energy Conversion Management, Vol.43(2002), 1349-1361. https://doi.org/10.1016/S0196-8904(02)00020-1
  7. Hwang, C. H. and A. C. H. Wu, "A predictive system shutdown method for energy saving of event-driven computation", ACM Transactions on Design Automation and Electronic Systems, Vol.5, No.2(2002), 226-241.
  8. Indraganti, M. and K. D. Rao, "Effect of age, gender, economic group and tenure on thermal comfort : A field study in residential buildings in hot and dry climate with seasonal variations", Energy and Buildings, Vol.42, No.3(2010), 273-281. https://doi.org/10.1016/j.enbuild.2009.09.003
  9. James, G., W. Peng and K. Deng, "Managing household wind-energy generation", IEEE Intelligent Systems, Vol.23, No.5(2008), 9-12.
  10. Kim, H. S., S. K. Kang, K. J. Park, C. W. Baek and J. S. Park, "Power management circuit for wireless ubiquitous sensor nodes powered by scavenged energy", Electronics Letters, Vol.45, No.7(2009), 373-374. https://doi.org/10.1049/el.2009.2477
  11. Kolokotsa, D., G. S. Stavrakakis, K. Kalaitzakis and Agoris, D. "Genetic algorithms optimized fuzzy controller for the indoor environmental management in buildings implemented using plc and local operating networks", Engineering Applications of Artificial Intelligence, Vol.15, No.5(2002), 417-428. https://doi.org/10.1016/S0952-1976(02)00090-8
  12. Kwon, O., K. Yoo and E. Suh, "UbiDSS : a proactive intelligent decision support system as an expert system deploying ubiquitous computing technologies", Expert Systems with Applications, Vol.28(2005), 149-161. https://doi.org/10.1016/j.eswa.2004.08.007
  13. Le, K., O. Bilgir, R. Bianchini, M. Martonosi and T. D. Nguyen, "Managing the cost, energy consumption, and carbon footprint of internet services", SIGMETRICS'10, (2010), 357-358.
  14. Lindley, S. E., M. Glancy, R. Harper, D. Randall and N. Smyth, "Oh and how things just don't change, the more they stay the same : Reflections on SenseCam images 18 months after capture", International Journal of Human-Computer Studies, Vol.69, No.5(2011), 311-323. https://doi.org/10.1016/j.ijhcs.2010.12.010
  15. Masoso, O. T. and L. J. Groblera, "The dark side of occupant's behaviour on building energy use", Energy and Buildings, Vol.42, No.2 (2010), 173-177. https://doi.org/10.1016/j.enbuild.2009.08.009
  16. Mavrotas, G., K. Florios and D. Vlachou, "Energy planning of a hospital using mathematical programming and Monte Carlo simulation for dealing with uncertainty in the economic parameters", Energy Conversion and Management, Vol.51(2010), 722-731. https://doi.org/10.1016/j.enconman.2009.10.029
  17. Min, X., W. Shi, C. Jiang and Z. Ying, "Energy efficient clustering algorithm for maximizing lifetime of wireless sensor networks", AEU : International Journal of Electronics and Communications, Vol.64, No.4(2010), 289-298. https://doi.org/10.1016/j.aeue.2009.01.004
  18. Mok, H., S. Son, J. H. Hong and S. Kim, "An approach for energy-aware management in ubiquitous home network environment", Lecture Notes in Computer Science, Vol.4761 (2007), 293-300.
  19. Moriarty, P. and D. Honnery, "A human needs approach to reducing atmospheric carbon", Energy Policy, Vol. 38(2010), 695-700. https://doi.org/10.1016/j.enpol.2009.10.043
  20. Mozer, M. C., "The neural network house : an environment that adapts to its inhabitants", Proceedings of the American Association for Artificial Intelligence Spring Symposium on Intelligent Environments, Menlo Park, CA, (1998), 110-114.
  21. Munir, S. A., X. Dongliang, C. Canfeng and J. Ma, "Service discovery in wireless sensor networks: protocols and classifications", Proceedings of the 11th international conference on Advanced Communication Technology, (2009), 1007-1011.
  22. NTT Japan. Bluebird Project, http://www.ntts.co.jp/java/bluegrid/en/, 2003.
  23. Oliver, J. Y., R. Amirtharajah, V. Akella, R. Geyer and F. T. Chong, "Life cycle awareness computing : reusing silicon technology", Computer, Vol.40, No.12(2007), 56-61.
  24. Oliver, N., A. Garg and E. Horvitz, "Layered representations for learning and inferring office activity from multiple sensory channels", Computer Vision and Image Understanding, Vol.96, No.2(2004), 163-180. https://doi.org/10.1016/j.cviu.2004.02.004
  25. Rahul, C. and J. Rabaey, "Energy aware routing for low energy ad hoc sensor networks", IEEE Wireless Communications and Networking Conference (WCNC), Orlando, FL, (2002), 350-355.
  26. Schiele, G., C. Becker and K. Rothermel, "Energyefficient cluster-based service discovery for Ubiquitous Computing", Proceedings of the 11th workshop on ACM SIGOPS European workshop : beyond the PC, Leuven, Belgium. 2004.
  27. Stojanovic, D., Context-Aware Mobile and Ubiquitous Computing for Enhanced Usability, Premier Reference Source, 2009.
  28. Sundarama, M., M. J. Smitha, D. A. Revickib, B. Elswickc and L. Millerd, "Rasch analysis informed the development of a classification system for a diabetes specific preferencebased measure of health", Journal of Clinical Epidemiology, Vol.62, No.8(2009), 845-856. https://doi.org/10.1016/j.jclinepi.2009.01.020
  29. Tentori, M. and J. Favela, "Activity-awareness computing for healthcare", IEEE Pervasive Computing, (2008), 51-57.
  30. Ueno, T., R. Inada, O. Saeki and K. Tsuji, "Effectiveness of an energy-consumption information system for residential buildings", Applied Energy, Vol.83(2006), 868-883. https://doi.org/10.1016/j.apenergy.2005.09.004
  31. Vykoukal, J., M. Wolf and R. Beck, "Does green IT matter? Analysis of the relationship between green IT and grid technology from a resource-based view perspective", Proceedings of the PACIS 2009, (2009), 51.
  32. Wu, S. and P. Noy, "A conceptual design of a wireless sensor actuator system for optimizing energy and well-being in buildings", Intelligent Buildings International, Vol.2(2010), 41-56. https://doi.org/10.3763/inbi.2009.0032
  33. Wu, Y., X. Li, Y. Liu and W. Lou, "Energy-efficient wake-up scheduling for data collection and aggregation", IEEE Transactions on Parallel and Distributed Systems, Vol.21, No.2 (2010), 275-287. https://doi.org/10.1109/TPDS.2009.45
  34. Yau, S. S. and F. Karim, "An energy-efficient object discovery protocol for context-sensitive middleware for ubiquitous computing", IEEE Transactions on Parallel and Distributed Systems, Vol.14, No.11(2003), 1074-1085. https://doi.org/10.1109/TPDS.2003.1247669