Sensor-Cloud Computing: Novel Applications and Research Problems

  • Yu-Hsn Liu
  • Kok-Leong Ong
  • Andrzej Goscinski
Part of the Communications in Computer and Information Science book series (CCIS, volume 294)

Abstract

Recent developments in sensor networks and cloud computing saw the emergence of a new platform called sensor-clouds. While the proposition of such a platform is to virtualise the management of physical sensor devices, we are seeing novel applications been created based on a new class of social sensors. Social sensors are effectively a human-device combination that sends torrent of data as a result of social interactions and social events. The data generated appear in different formats such as photographs, videos and short text messages. Unlike other sensor devices, social sensors operate on the control of individuals via their mobile devices such as a phone or a laptop. And unlike other sensors that generate data at a constant rate or format, social sensors generate data that are spurious and varied, often in response to events as individual as a dinner outing, or a news announcement of interests to the public. This collective presence of social data creates opportunities for novel applications never experienced before. This paper discusses such applications as a result of utilising social sensors within a sensor-cloud environment. Consequently, the associated research problems are also presented.

Keywords

Sensor Network Research Problem Sentiment Analysis Short Message Twitter User 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. 1.
    Akyildiz, I.F., Su, W., Sankarasubramaniam, Y., Cayirci, E.: A Survey on Sensor Networks. IEEE Communications Magazine 40(8), 102–114 (2002)CrossRefGoogle Scholar
  2. 2.
    Hassan, M.M., Song, B., Huh, E.-N.: A Framework of Sensor-Cloud Integration Opportunities and Challenges. In: Proc. 3rd Int. Conf. on Ubiquitous Information Management and Communication, New York, USA, pp. 618–626 (2009)Google Scholar
  3. 3.
    Schilit, B., Adams, N., Want, R.: Context-Aware Computing Applications. In: Proc. Workshop on Mobile Computing Systems and Applications, pp. 85–90. IEEE Computer Society (1994)Google Scholar
  4. 4.
    Liu, Y.-H., Ren, Y., Dew, R.: Monetising User Generated Content Using Data Mining Techniques. In: Proc. 8th Australiasian Data Mining Conference, Melbourne, Australia, pp. 75–81 (2009)Google Scholar
  5. 5.
    Cha, M., Kwak, H., Rodriguez, P., Ahn, Y.-Y., Moon, S.: I Tube, you Tube, everybody Tubes: Analyzing the World’s Largest User Generated Content Video System. In: Proc. 7th ACM SIGCOMM Int. Conf. on Internet Measurement, New York, NY, USA, pp. 1–14 (2007)Google Scholar
  6. 6.
  7. 7.
    Moore, A.: PBL Considers Further Media Sell-off, http://www.abc.net.au/lateline/business/items/200705/s1935762.htm
  8. 8.
    Hearst, M.A.: Direction-based Text Interpretation as an Information Access Refinement. In: Jacobs, P. (ed.) Text-Based Intelligent Systems. Lawrence Erlbaum Associates (1992)Google Scholar
  9. 9.
    Das, S.R., Chen, M.Y.: Yahoo for Amazon! Sentiment Extraction from Small Talk on the Web. Management Science 53(9), 1375–1388 (2007)CrossRefGoogle Scholar
  10. 10.
    Tong, R.M.: An Operational System for Detecting and Tracking Opinions in on-line discussion. In: Proc. SIGIR 2001 Workshop on Operational Text Classification in Conj. in Conjunction with ACM SIGIR 2001, New Orleans, USA (2001)Google Scholar
  11. 11.
    Turney, P.D.: Thumbs Up or Thumbs Down? Semantic Orientation Applied to Unsupervised Classification of Reviews. In: Isabelle, P. (ed.) Proc. Association for Computational Linguistics 40th Anniversary Meeting, Philadelphia, PA, USA, pp. 417–424 (2002)Google Scholar
  12. 12.
    Ding, X., Liu, B., Zhang, L.: Entity Discovery and Assignment for Opinion Mining Applications. In: Proc. 15th ACM SIGKDD Int. Conf. on Knowledge Discovery and Data Mining, Paris, France, pp. 1125–1134 (2009)Google Scholar
  13. 13.
    Wang, W., Yu, Y., Zhang, J.: A New SVM Based Emotional Classification of Images. Journal of Electronics 22(1), 98–104 (2005)Google Scholar
  14. 14.
    Moore, S.: Gartner Says Context-Aware Computing Will Be a $12 Billion Market By 2012 (2012), http://www.gartner.com/it/page.jsp?id=1229413
  15. 15.
    Higginbotham, S.: Sensor Networks Top Social Networks for Big Data, Bloomberg BusinessWeek, http://www.businessweek.com/technology/content/sep2010/tc20100914_284956.htm
  16. 16.
    Ostrow, A.: Japan Earthquake Shakes Twitter Users... And Beyonce, http://mashable.com/2009/08/12/japan-earthquake/
  17. 17.
    Goldstein, J., Mittal, V., Carbonell, J., Kantrowitz, M.: Multi-Document Summarization by Sentence Extraction. In: Proc. 2000 NAACL-ANLP Workshop on Automatic Summarizatio in Conj. Association for Computational Linguistics, Stroudsburg, USA, pp. 40–48 (2000)Google Scholar
  18. 18.
    Park, S., Lee, J.-H., Kim, D.-H., Ahn, C.-M.: Multi-document Summarization Based on Cluster Using Non-negative Matrix Factorization. In: van Leeuwen, J., Italiano, G.F., van der Hoek, W., Meinel, C., Sack, H., Plášil, F. (eds.) SOFSEM 2007. LNCS, vol. 4362, pp. 761–770. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  19. 19.
    Han, Y., Janciak, I., Brezany, P., Goscinski, A.: The CloudMiner - Moving Data Mining into Computational Clouds. In: Aloisio, G., Fiore, S. (eds.) Grid and Cloud Database Management, pp. 193–214. Springer (2011)Google Scholar
  20. 20.
    McCarthy, C.: Nielsen: Twitter’s Growing Really, Really, Really, Really Fast. CNet News, http://news.cnet.com/8301-13577_3-10200161-36.html

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Yu-Hsn Liu
    • 1
  • Kok-Leong Ong
    • 2
  • Andrzej Goscinski
    • 2
  1. 1.Department of Computer Science and Computer EngineeringLaTrobe UniversityBundooraAustralia
  2. 2.School of Information TechnologyDeakin UniversityBurwoodAustralia

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