A Review on Performance Analysis and Improvement of Internet of Things Application

Authors

  • Bharti AK Department of Computer Science, Maharishi University of Information Technology, Lucknow, India
  • Negi R Department of Computer Science, Maharishi University of Information Technology, Lucknow, India
  • Verma DK Department of Computer Science, JNPG College, University of Lucknow, Lucknow, India

DOI:

https://doi.org/10.26438/ijcse/v7i2.367371

Keywords:

IOT, Big Data, BDSC

Abstract

Big data and IoT is two different challenging terms in IT industry. Currently, IoT is an emerging technology and is being used various application for development and research. Big Data Stream Computing (BDSC) is an emerging feature for dealing a real-time data streams and providing faster decisions. BDSC is being used in much of the real time IOT applications. The main objective of the work is to review and measure the performance analysis of real-time IoT application data processing using BDSC platform.

References

[1] SWDS Li, J., Bao, Z. and Z. Li, “Modeling Demand Response Capability by Internet Data Centers Processing Batch Computing Jobs”, IEEE Trans. on Smart Grid, Vol. 6, No. 2, pp. 737–747, 2015.

[2] Liu, X., N. Iftikhar and X. Xie, “Survey of Real-Time Processing Systems for Big Data”, 18th Int. Database Engineering and Applications Symposium, New York, pp. 356–361, USA, 2014.

[3] Liu, X., N. Iftikhar and X. Xie, “Survey of Real-Time Processing Systems for Big Data”, 18th Int. Database Engineering and Applications Symposium, New York, pp. 356–361, USA, 2014

[4] Shao, H., L. Rao, Z. Wang, X. Liu, Z. Wang and K. Ren., “Optimal Load Balancing and Energy Cost Management for Internet Data Centers in Deregulated Electricity Markets”, IEEE Trans. Parall. Distr. Syst., Vol. 25, No. 10, pp. 2659–2669 , 2014.

[5] Sharifi, M., S. Shahrivari and H. Salimi, “PASTA: A Power-aware Solution to Scheduling of Precedence-constrained Tasks on Heterogeneous Computing Resources”, J. Computing, Vol. 95, No. 1, pp. 67–88, 2013.

[6] Singh, K. and R. Kaur, “Hadoop: Addressing Challenges of Big Data”, 2014 IEEE Int. Advance Computing Conf., Navi Mumbai, pp. 686-689, India, 2014.

[7] Sinnen, O., A. Tok and M. Khan, “Contention-aware Scheduling with Task Duplication”, J. Parall. Distr. Comput., Vol. 71, No. 1, pp. 77–86, 2011.

[8] Sun, D., G. Fu, X. Liu and H. Zhang, “Optimizing Data Stream Graph for Big Data Stream Computing in Cloud Datacenter Environments”, Int. J. of Advancements in Computing Technology, Vol. 6, No. 5, pp. 53–65, 2014.

[9] K. Parimala, G. Rajkumar, A. Ruba, S. Vijayalakshmi, "Challenges and Opportunities with Big Data", International Journal of Scientific Research in Computer Science and Engineering, Vol.5, Issue.5, pp.16- 20, 2017

[10] Sun, D., G. Zhang, S. Yang, Zheng W., S. U.Khan and K. Li, “Re-stream: Realtime and Energy-efficient Resource Scheduling in Big Data Stream Computing Environments”, Information Sciences, No. 319, pp. 92-112, 2015.

[11] Mantripatjit Kaur, Anjum Mohd Aslam, "Big Data Analytics on IOT: Challenges, Open Research Issues and Tools", International Journal of Scientific Research in Computer Science and Engineering, Vol.6, Issue.3, pp.81-85, 2018

[12] V.K. Gujare, P. Malviya, "Big Data Clustering Using Data Mining Technique", International Journal of Scientific Research in Computer Science and Engineering, Vol.5, Issue.2, pp.9-13, 2017.

[13] Shilpa Manjit Kaur, “BIG Data and Methodology- A review” ,International Journal of Advanced Research in Computer Science and Software Engineering, Volume 3, Issue 10, October 2013.

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Published

2019-02-28
CITATION
DOI: 10.26438/ijcse/v7i2.367371
Published: 2019-02-28

How to Cite

[1]
A. K. Bharti, R. Negi, and D. K. Verma, “A Review on Performance Analysis and Improvement of Internet of Things Application”, Int. J. Comp. Sci. Eng., vol. 7, no. 2, pp. 367–371, Feb. 2019.