Advertisement

Ubiquitous Connections: The Internet of People and Things

  • Seng W. Loke
Chapter
Part of the SpringerBriefs in Computer Science book series (BRIEFSCOMPUTER)

Abstract

This chapter introduces a range of technology trends, including Cloud Computing, Internet of Things, Device Mesh, Big Data, Wearable Computing, Crowd Computing, Crowdsourcing, Culture of Sharing, Collective Computing, and Swarm Dynamics, and gives an outline of the book. Five perspectives are introduced, namely, crowd+cloud machines, extreme cooperation, scalable context-awareness, drone services, and social links in mobile crowds.

Keywords

Mobile Device Cloud Computing Mobile Cloud Mobile Cloud Computing Swarm System 
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.

References

  1. 1.
    Gregory D. Abowd. Beyond weiser: From ubiquitous to collective computing. Computer, 49(1):17–23, 2016.Google Scholar
  2. 2.
    Roland Bouffanais. Design and Control of Swarm Dynamics. Springer, 2016.CrossRefzbMATHGoogle Scholar
  3. 3.
    Abhishek Chandra, Jon Weissman, and Benjamin Heintz. Decentralized edge clouds. IEEE Internet Computing, 17(5):70–73, September 2013.Google Scholar
  4. 4.
    Robin Chase. Peers Inc: How People and Platforms Are Inventing the Collaborative Economy and Reinventing Capitalism. PublicAffairs, 2015.Google Scholar
  5. 5.
    Cen Chen, Shih-Fen Cheng, Aldy Gunawan, and Archan Misra. Traccs: Trajectory-aware coordinated urban crowd-sourcing. In Conference on Human Computation and Crowdsourcing (HCOMP?14), Pittsburgh, USA, November 2014.Google Scholar
  6. 6.
    Dingxiong Deng, Cyrus Shahabi, Ugur Demiryurek, and Linhong Zhu. Task selection in spatial crowdsourcing from worker’s perspective. Geoinformatica, 20(3):529–568, July 2016.Google Scholar
  7. 7.
    Nathan Eagle. Txteagle: Mobile crowdsourcing. In Proceedings of the 3rd International Conference on Internationalization, Design and Global Development: Held As Part of HCI International 2009, IDGD ’09, pages 447–456, Berlin, Heidelberg, 2009. Springer-Verlag.Google Scholar
  8. 8.
    Niroshinie Fernando, Seng W. Loke, and Wenny Rahayu. Mobile cloud computing: a Survey. Future Gener. Comput. Syst., 29(1):84–106, January 2013.Google Scholar
  9. 9.
    Frank H.P. Fitzek and Marcos D. Katz. Mobile Clouds: Exploiting Distributed Resources in Wireless, Mobile and Social Networks. Wiley Publishing, 1st edition, 2014.Google Scholar
  10. 10.
    R.K. Ganti, Fan Ye, and Hui Lei. Mobile crowdsensing: current state and future challenges. Communications Magazine, IEEE, 49(11):32–39, November 2011.Google Scholar
  11. 11.
    Neil Gershenfeld. When Things Start to Think. Henry Holt and Co., Inc., New York, NY, USA, 1999.Google Scholar
  12. 12.
    Aakar Gupta, William Thies, Edward Cutrell, and Ravin Balakrishnan. mclerk: enabling mobile crowdsourcing in developing regions. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pages 1843–1852, Austin, Texas, USA., May 5-10 2012. ACM.Google Scholar
  13. 13.
    Jeff Howe. The rise of crowdsourcing. Wired magazine, 14(6):1–4, 2006.Google Scholar
  14. 14.
    Mike Kuniavsky. Smart Things: Ubiquitous Computing User Experience Design: Ubiquitous Computing User Experience Design. Morgan Kaufmann Publishers Inc., San Francisco, CA, USA, 2010.Google Scholar
  15. 15.
    G. Li, J. Wang, Y. Zheng, and M. J. Franklin. Crowdsourced data management: A survey. IEEE Transactions on Knowledge and Data Engineering, 28(9):2296–2319, Sept 2016.Google Scholar
  16. 16.
    Adam Marcus and Aditya Parameswaran. Crowdsourced data management: Industry and academic perspectives. Found. Trends databases, 6(1-2):1–161, December 2015.Google Scholar
  17. 17.
    Viktor Mayer-Schnberger. Big Data: A Revolution That Will Transform How We Live, Work and Think. Viktor Mayer-Schnberger and Kenneth Cukier. John Murray Publishers, UK, 2013.Google Scholar
  18. 18.
    Pietro Michelucci and Janis L. Dickinson. The power of crowds. Science, 351(6268):32–33, 2015.Google Scholar
  19. 19.
    Prayag Narula, Philipp Gutheim, David Rolnitzky, Anand Kulkarni, and Bjoern Hartmann. Mobileworks: A mobile crowdsourcing platform for workers at the bottom of the pyramid. Human Computation, 11:11, 2011.Google Scholar
  20. 20.
    J. Ren, Y. Zhang, K. Zhang, and X. Shen. Exploiting mobile crowdsourcing for pervasive cloud services: challenges and solutions. Communications Magazine, IEEE, 53(3):98–105, March 2015.Google Scholar
  21. 21.
    David Rose. Enchanted Objects: Innovation, Design, and the Future of Technology. Simon and Schuster, 2014.Google Scholar
  22. 22.
    M. Satyanarayanan, P. Bahl, R. Caceres, and N. Davies. The case for vm-based cloudlets in mobile computing. IEEE Pervasive Computing, 8(4):14–23, Oct 2009.Google Scholar
  23. 23.
    Daniel Sui, Sarah Elwood, and Michael Goodchild, editors. Crowdsourcing Geographic Knowledge: Volunteered Geographic Information (VGI) in Theory and Practice. Springer, 2013.Google Scholar
  24. 24.
    Arun Sundararajan. The Sharing Economy: The End of Employment and the Rise of Crowd-Based Capitalism. MIT Press, 2016.Google Scholar
  25. 25.
    Hien To, Cyrus Shahabi, and Leyla Kazemi. A server-assigned spatial crowdsourcing framework. ACM Trans. Spatial Algorithms Syst., 1(1):2:1–2:28, July 2015.Google Scholar
  26. 26.
    Umair ul Hassan and Edward Curry. Efficient task assignment for spatial crowdsourcing. Expert Syst. Appl., 58(C):36–56, October 2016.Google Scholar
  27. 27.
    Tingxin Yan, Matt Marzilli, Ryan Holmes, Deepak Ganesan, and Mark Corner. mcrowd: A platform for mobile crowdsourcing. In Proceedings of the 7th ACM Conference on Embedded Networked Sensor Systems, SenSys ’09, pages 347–348, New York, NY, USA, 2009. ACM.Google Scholar

Copyright information

© The Author(s) 2017

Authors and Affiliations

  • Seng W. Loke
    • 1
  1. 1.School of Information TechnologyDeakin UniversityBurwoodAustralia

Personalised recommendations