Towards Fog Computing based Cloud Sensor Integration for Internet of Things

IJCSEC Front Page

Abstract:
The Internet of Things (IoT) interconnects various identifiable devices within Internet for sensing and monitoring processes. In particular, Wireless Sensor Network (WSN) is formed by connecting identifiable devices like smart sensor, embedded CPU (Central Processing Unit), low power radios, to the internet through gateway that interfaces WSN to the internet. To handle the large amount of data generated by devices in IOT environment, cloud infrastructure provides Sensing as a Service(SeaaS) which can make sensor data available in cloud infrastructure for sensing and observing the environment conditions. Today’s cloud models are not designed for the volume, variety, and velocity of data that the IoT generates. Handling the volume, variety, and velocity of IoT data requires a new computing model. In this paper, we surveyed some typical applications of Sensor Network using Cloud computing as backbone spotlighting on fog computing to overcome some of the management issues of cloud computing and to handle time-sensitive data. Since Cloud computing provides plenty of application, platforms and infrastructure over the Internet, it may combined with Sensor network and fog computing in the application areas such as environmental monitoring, weather forecasting, transportation business, healthcare, military application etc which requires to handle within a second.

Keywords: WSN,cloud computing, fog computing, CSaaS, Internet of Things.

References:

  1. Ulmer, L.Alkalai and S.Yalamanchili, Wireless distributed sensor networks for in-situ exploration of mars, Work in progress for NASA Technical Report. Available in: http://users.ece.gatech.edu.
  2. J. Gubbi, R. Buyya, S. Marusic, and M. Palaniswami, “Internet of Things (IoT): a vision, architectural elements, and future directions,”Future Generation Computer Systems, vol.29, no.7, pp.1645–1660, 2013.
  3. R.Khan, S.U.Khan, R.Zaheer, and S.Khan, “Future internet: the internet of things architecture, possible applications and key challenges,” in Proceedings of the 10th IEEE International Conference on Frontiers of Information Technology (FIT’12), Islamabad, Pakistan, ), pp.257-260,December 2012.
  4. X. Sheng, J. Tang, X. Xiao, and G. Xue, “Sensing as a service: challenges, solutions and future directions, ”IEEE Sensors Journal,vol.13,no.10, pp. 3733–3741,2013.
  5. M. A. E. Al-Fagih, F. M. Al-Turjman, W. M. Alsalih, and H. S. Hassanein, “Priced public sensing framework for heterogeneous IoT architectures, ”IEEE Transactions on Emerging Topics in Computing,vol.1,no.1,pp.133–147,2013.
  6. D.B.Hoang and L.Chen, “Mobile Cloud for Assistive Health-care(MoCAsH),” in Proceedings of the IEEE Asia-Pacific Services Computing Conference (APSCC ’10), Hangzhou, China, pp. 325–332, December 2010.
  7. B. B. P. Rao, P. Saluia, N. Sharma, A. Mittal, and S. V. Sharma, “Cloud computing for Internet of Things & sensing based applications, ”in Proceedings of the 6th International Conference on Sensing Technology (ICST ’12), Kolkata, India, pp. 374–380, December 2012.
  8. J. Cheng, R.K. Balan, M. Satyanarayanan, “Exploiting rich mobile environments,Technical Report”, 2005.
  9. Alamri, A., Ansari, W, S., Hassan, M, M., Hossain, M, S., Alelaiwi, A., and Hossain, M, A., “A Survey on Sensor-Cloud: Architecture, Applications and Approaches”, International Journal of Distributed Sensor Networks, Vol.2013, pp.9-26, 2013.
  10. Dash, S, K., Sahoo, J, P., Mohapatra, S., and Pati, S, P., “Sensor-cloud: assimilation of wireless sensor network and the cloud”, Advances in Computer Science and Information Technology. Networks and Communications- Second International Conference, CCSIT 2012, Bangalore, India, Vol. 84, pp. 455-464, January 2-4, 2012.
  11. Dinh, H, T., Lee, C., Niyato, D., and Wang, P., “A Survey of Mobile Cloud Computing: Architecture, Applications, and Approaches”, Wireless Communications and Mobile Computing-Wiley Online Library, Vol: 13, Issue: 18, pp: 1587-1611, 2011.
  12. Gomathi, B.,Karthikeyan, K. and Saravana Balaji, B., “Epsilon-fuzzy dominance sort-based composite discrete artificial bee colony optimisation for multi-objective cloud task scheduling problem”, Int. J. Business Intelligence and Data Mining, Vol. 13, Nos. 1/2/3, pp.247–266,2018.
  13. Bar-Magen Numhauser, Jonathan, “Fog Computing introduction to a New Cloud Evolution”, Escrituras silenciadas: paisaje como historiografía. Spain: University of Alcala. pp. 111–126. ISBN 978-84-15595-84-7,2012.
  14. "IoT, from Cloud to Fog Computing". blogs@Cisco - Cisco Blogs. Retrieved 2017-04-07.
  15. "What Is Fog Computing? Webopedia Definition". www.webopedia.com. Retrieved 2017-04-07.