A Comparative Study of Clustering Techniques Used in Cloud Computing to Minimize the Adverse Environmental Impact

Authors

  • Raj R Dept. of Information Technology Rajkiya Engineering College, AmbedkarNagar
  • Vivekanand Dept. of Information Technology Rajkiya Engineering College, AmbedkarNagar
  • Shukla S Dept. of Information Technology Rajkiya Engineering College, AmbedkarNagar

DOI:

https://doi.org/10.26438/ijcse/v6i5.857860

Keywords:

Cloud Computing, Clustering, Cloud Data centers, Clustering Algorithm, K-Means Clustering, Map-Reduce, Resource Identification and Clustering

Abstract

Cloud Computing is a computing paradigm where various tasks are assigned to a combination of connections, software and services that can be accessed by the user over a network. The research paper aims to reach a theoretical notion of sustainable development with proposing an incentive for reducing global warming through effective clustering techniques and methods. This paper is a comparative study on k-means clustering, map-reduce technique and resource clustering used in cloud computing. The focus of the paper is to suggest better methodology for handling the events of cloud computing and possibly reducing the similar types of events by clustering them. This approach might lead to the reduction of carbon-dioxide gas (which is a greenhouse gas) by less usage of servers in cloud data centers. With the advent of IT services in cloud computing energy consumption it is necessary for the developing technology to progress towards sustainable development rather thrashing and harnessing energy from every possible means.

References

[1] K. Birman, “Networks and Cloud”, CS5412 Spring (Cloud Computing: Birman), 2015.

[2] R. K. Trivedi, R. Sharma, “Case Study on Environmental Impact of Cloud Computing”, IOSR-JCE e-ISSN: 2278-0661, p-ISSN: 2278-8727 Volume 16, Issue 2, Ver. VI, PP 81-86, 2014.

[3] M. Arif, T. Mahmood, “Cloud Computing and its Environmental Effects”, International Journal of Grid Distribution Computing Vol.8, No.1, pp.279-286, 2015.

[4] A. More, P. Kanungo, "Use of Cloud Computing for Implementation of e-Governance Services", International Journal of Scientific Research in Computer Science and Engineering, Vol.5, Issue.3, pp.115-118, 2017.

[5] Y. G. Patil, P. S. Deshmukh, "A Review: Mobile Cloud Computing: Its Challenges and Security", Vol.06, Issue.01, pp.11-13, 2018.

[6] M. K. Saggi, A. S. Bhatia, “A Review on Mobile Cloud Computing: Issues, Challenges and Solutions”, International Journal of Advanced Research in Computer and Communication Engineering, 2015.

[7] R. V. Dharmadhikari, S. S. Turambekar, S. C. Dolli, P K Akulwar, "Cloud Computing: Data Storage Protocols and Security Techniques", International Journal of Scientific Research in Computer Science and Engineering, Vol.6, Issue.2, pp.113-118, 2018.

[8] M. Gattulli, M. Tornatore, R. Fiandra, A. Pattavina, “Low- Carbon Routing Algorithms for Cloud Computing Services in IP-over-WDM Networks”, IEEE ICC Optical Network and Systems, 2012.

[9] Malathy, G. R. Somasundaram, K. Duraiswamy, “Performance Improvement in Cloud Computing Using Resource Clustering”, Journal of Computer Science 9 (6): 671-677, ISSN: 1549-3636, 2013.

[10] D.K. Sharma, S.K. Dhurandher, A. Kumar, A. Kumar, A.K. Jha, “Cloud Computing based Routing Protocol for Infrastructure-based Opportunistic Networks”, CAITFS Division of Information Technology, 2016.

[11] S.N. Bushra, A.C. Sekar, “An Efficient Clustering Method for Incremental Cloud Data”, IJARCSSE ISSN: 2277128X, 2014.

[12] E. Sarkar, C.H Sekhar, “Organizing Data in Cloud using Clustering Approach”, International Journal of Scientific & Engineering Research, Volume 5, Issue 5, 2014.

[13] I. Singh, P. Dwivedi, T. Gupta, P. G. Shynu, “Enhanced K-means clustering with encryption on cloud”, IOP Conf. Series: Materials Science and Engineering 263, 042057, 14th ICSET, 2017.

[14] S.Y Kim, J. Bottleson, J. Jin, P. Bindu, S.C. Sakhare, J.S Spisak, “Power Efficient Map Reduce Workload Acceleration using Integrated GPU”, IEEE First International Conference on Big Data Computing Service and Applications, 2015.

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Published

2025-11-13
CITATION
DOI: 10.26438/ijcse/v6i5.857860
Published: 2025-11-13

How to Cite

[1]
R. Raj, V. Vivekanand, and S. Shukla, “A Comparative Study of Clustering Techniques Used in Cloud Computing to Minimize the Adverse Environmental Impact”, Int. J. Comp. Sci. Eng., vol. 6, no. 5, pp. 857–860, Nov. 2025.

Issue

Vol. 6 No. 5 (2018): IJCSE May Edition

Section

Review Article

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