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Integration of Wireless Sensor Networks with Cloud Towards Efficient Management in IoT: A Review

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Advances in Data and Information Sciences

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 94))

Abstract

Internet-of-things (IoT) became very popular in today’s research. IoT means all devices of a particular system should be connected with each other through the internet. Cloud Computing and Wireless Sensor Networks (WSN) are integrated for efficient management in IoT. This integration is known as Sensor Cloud. This technology has a lot of applications due to the continuous development of information and communication technology. Although sensor cloud has several advantages still it has many research challenges like energy efficiency, security, QoS, etc. The wireless sensor network is the network of sensors which operate on battery. Reducing energy consumption and communication overhead are important issues of wireless sensor networks. Efficient management of WSN and cloud results in efficient management of IoT. This paper presents a survey on efficient management of IoT with sensor cloud.

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References

  1. Dwivedi, R. K., Singh, S., & Kumar, R. (2019). Integration of wireless sensor networks with cloud: A review. In 2019 9th IEEE International Conference on Cloud Computing, Data Science & Engineering (Confluence) (pp. 115–120). Noida, India.

    Google Scholar 

  2. Dwivedi, R. K., & Kumar, R. (2018). Sensor cloud: Integrating wireless sensor networks with cloud computing. In 2018 5th IEEE Uttar Pradesh Section International Conference on Electrical, Electronics and Computer Engineering (UPCON) (pp. 820–825). Gorakhpur, India.

    Google Scholar 

  3. Dwivedi, R. K., Saran, M., & Kumar, R. (2019). A survey on security over sensor-cloud. In 2019 9th IEEE International Conference on Cloud Computing, Data Science & Engineering (Confluence) (pp. 31–37). Noida, India.

    Google Scholar 

  4. O’Brien, M. (2008). Remote telemonitoring—A preliminary review of current evidence. European Center for Connected Health (pp. 76–82).

    Google Scholar 

  5. Lazarescu, M. (2013). Design of a WSN platform for long-term environmental monitoring for IoT applications (pp. 45–54). IEEE Journal: Emerging and Selected Topics in Circuits and Systems.

    Google Scholar 

  6. Ponmagal, R. S., & Raja, J. (2011). An extensible cloud architecture model for heterogeneous sensor services. International Journal of Computer Science and Information Security, 9(1), 227–233.

    Google Scholar 

  7. Dwivedi, R. K., Sharma, P. & Kumar, R. (2018). A scheme for detection of high transmission power based wormhole attack in WSN. In 2018 5th IEEE Uttar Pradesh Section International Conference on Electrical, Electronics and Computer Engineering (UPCON) (pp. 826–831). Gorakhpur, India.

    Google Scholar 

  8. Dwivedi, R. K., Sharma, P. & Kumar, R. (2018). Detection and prevention analysis of wormhole attack in wireless sensor network. In 2018 8th International Conference on Cloud Computing, Data Science & Engineering (Confluence) (pp. 727–732). Noida, India.

    Google Scholar 

  9. Dwivedi, R. K., Pandey, S., & Kumar, R. (2018). A study on machine learning approaches for outlier detection in wireless sensor network. In 2018 8th International Conference on Cloud Computing, Data Science & Engineering (Confluence) (pp. 189–192). Noida, India.

    Google Scholar 

  10. Sharma, P., & Dwivedi, R. K. (2019). Detection of high transmission power based wormhole attack using received signal strength indicator (RSSI). In S. Verma, R. Tomar, B. Chaurasia, V. Singh, & J. Abawajy (Eds.), Communication, networks and computing. CNC 2018. Communications in computer and information science (Vol. 839, pp. 142–152). Singapore: Springer.

    Google Scholar 

  11. Kumar, P., Kumar, R., Kumar, S., & Dwivedi, R. K. (2010, November). Improved modified reverse AODV protocol. International Journal of Computer Applications—IJCA, 12(4), 22–26.

    Google Scholar 

  12. Dwivedi, R. K., Tiwari, R., Rani, D., & Shadab, S. (2012). Modified reliable energy aware routing protocol for wireless sensor network. International Journal of Computer Science & Engineering Technology—IJCSET, 3(4), 114–118.

    Google Scholar 

  13. Verma, K., & Dwivedi, R. K. (2016). A review on energy efficient protocols in wireless sensor networks. International Journal of Current Engineering and Scientific Research—IJCESR, 3(12), 28–34.

    Google Scholar 

  14. Verma, K., & Dwivedi, R. K. (2017). AREDDP: Advance reliable and efficient data dissemination protocol in wireless sensor networks. In 2017 International Conference on Innovations in Information, Embedded and Communication Systems (ICIIECS) (pp. 1–4). Coimbatore.

    Google Scholar 

  15. Dwivedi, R. K. (2012). From grid computing to cloud computing & security issues in cloud computing. Technia: International Journal of Computing Science and Communication Technologies—IJCSCT, 5(1), 805–809.

    MathSciNet  Google Scholar 

  16. Naik, A. K., & Dwivedi, R. K. (2016). A review on use of data mining methods in wireless sensor network. International Journal of Current Engineering and Scientific Research—IJCESR (ISSN PRINT: 2393–8374, ISSN ONLINE: 2394-0697), 3(12), 13–20.

    Google Scholar 

  17. Agarwal, A., Maddhesiya, S., Singh, P., & Dwivedi, R. K. (2012). A long endurance policy (LEP): An improved swap aware garbage collection for NAND flash memory used as a swap space in electronic devices. International Journal of Scientific and Engineering Research—IJSER, 3(6), 412–417.

    Google Scholar 

  18. Chaudhary, M. K., Kumar, M., Rai, M., & Dwivedi, R. K. (2011, January). A modified algorithm for buffer cache management. International Journal of Computer Applications—IJCA, 12(12), 47–49.

    Google Scholar 

  19. European Commission. (2013). Definition of a research and innovation policy lever aging cloud computing and IoT combination. Tender specifications, SMART 2013/0037.

    Google Scholar 

  20. Jeffery, K. (2014). Keynote: CLOUDs: A large virtualisation of small things. In The 2nd International Conference on Future Internet of Things and Cloud (FiCloud-2014).

    Google Scholar 

  21. He, W., Yan, G., Xu, L. D. (2014). Developing vehicular data cloud services in the IoT environment. IEEE Transactions on Industrial Informatics, 10(2), 1587–1595.

    Google Scholar 

  22. Lee, K., Murray, D., Hughes, D., & Joosen, W. (2010). Extending sensor networks into the cloud using Amazons web services. In IEEE International Conference on Networked Embedded Systems for Enterprise Applications (NESEA) (pp. 1–7).

    Google Scholar 

  23. Madden, S. R., & Franklin, M. J. (2016). Fjording the stream: An architecture for queries over streaming sensor data. In The 18th International Conference on Data Engineering (pp. 106–112).

    Google Scholar 

  24. Gnawali, O., Fonseca, R., Jamieson, K., Moss, D., & Levis, D. (2009). Collection tree protocol. In The 7th ACM Conference on Embedded Networked Sensor Systems (SenSys) (pp. 89–95).

    Google Scholar 

  25. Sudarshan, K. S. (2010). A comprehensive study of mobile sensing and cloud services. In IEEE Conference (pp. 117–123).

    Google Scholar 

  26. Deborah, E. (2016). Participatory sensing: Applications and architecture [internet predictions]. In IEEE conference on Internet Computing (pp. 12–42).

    Google Scholar 

  27. Alessio, B. (2016). Integration of cloud computing and internet of things: A survey. Future Generation Computer Systems, 56, 684–700.

    Article  Google Scholar 

  28. Nair, G. N., Morrow, P. J. & Parr, G. (2011). Design considerations for a self-managed wireless sensor cloud for emergency response scenario (pp. 189–195).

    Google Scholar 

  29. Dash, K. S. (2012). Sensor-cloud: Assimilation of wireless sensor network and the cloud. In International Conference on Computer Science and Information Technology (pp. 193–199). Springer.

    Google Scholar 

  30. Dinh, H. T. (2013). A survey of mobile cloud computing: Architecture, applications, and approaches. Wireless Communications and Mobile Computing, 1587–1611.

    Google Scholar 

  31. Dash, K. S., Mohapatra, S., & Pattnaik, P. K. (2010). A survey on applications of wireless sensor network using cloud computing. International Journal of Computer Science & Emerging Technologies, 50–55.

    Google Scholar 

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Madan Mohan Malaviya University of Technology, Gorakhpur, UP, India

    Rajendra Kumar Dwivedi, Nikita Kumari & Rakesh Kumar

Authors
  1. Rajendra Kumar Dwivedi
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  2. Nikita Kumari
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  3. Rakesh Kumar
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Corresponding author

Correspondence to Nikita Kumari .

Editor information

Editors and Affiliations

  1. Smart Grid and Renewable Energy, University of Agder, Kristiansand, Norway

    Mohan L. Kolhe

  2. Department of Computer Science and Engineering, ABES Engineering College, Ghaziabad, Uttar Pradesh, India

    Shailesh Tiwari

  3. Department of Computer Science and Engineering, NIT Agartala, Tripura, India

    Munesh C. Trivedi

  4. Computer Science and Engineering, Motilal Nehru National Institute of Technology Allahabad, Prayagraj, India

    Krishn K. Mishra

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Dwivedi, R.K., Kumari, N., Kumar, R. (2020). Integration of Wireless Sensor Networks with Cloud Towards Efficient Management in IoT: A Review. In: Kolhe, M., Tiwari, S., Trivedi, M., Mishra, K. (eds) Advances in Data and Information Sciences. Lecture Notes in Networks and Systems, vol 94. Springer, Singapore. https://doi.org/10.1007/978-981-15-0694-9_10

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  • DOI: https://doi.org/10.1007/978-981-15-0694-9_10

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-15-0693-2

  • Online ISBN: 978-981-15-0694-9

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