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The Impact of Data Mining and SaaS-Cloud Computing: A Review

Yıl 2020, Cilt: 3 Sayı: 1, 23 - 35, 22.12.2020

Öz

Cloud Computing has emerged as a powerful paradigm that has successfully dominated network services in many application areas and significantly transformed the IT industry. In the Cloud Computing, all resources are available as services and accessible via the Internet. Software as a Serviceis considered as the king of service delivery models that enable end-users to access to any software or application as a service via the Internet, without local installation. Over the past decade, this model has been widely adopted by many organizations and individuals, leading to the production and accumulation of a huge amount of data stored in the Cloud from distributed nodes that must be recovered very efficiently. Software as a Service providers must be able to manage this data successfully, evaluate and improve the quality of their solutions in order to provide reliable and efficient services to users of Cloud services. On the other hand, Data Mining is a current trend in the field of data treatment that allows the extraction of useful and meaningful information from raw data. The integration of Data Mining techniques into Cloud Computing –Software as a Service -has become commonplace and can support the adequate provision of services by providing agility and rapid access to technology. This article introduces the basic concepts of Data Mining and Cloud Computing first, and discusses the coupling of the two paradigms. Then, it describes how Data Mining can be used and integrated to improve Software as a Service services in the Cloud. Finally, it reviews relevant and important research in this area.

Kaynakça

  • Tabii, işte referansları aralarında boşluk bırakarak ve numaraları `[ ]` kullanarak sıralanmış versiyon:
  • [1] S. Bandela, R. Gadde and S. Pabboju, "Survey on Cloud Computing Technologies and Security Threats", International journal of engineering research and technology, Volume 2, Issue 6, May 2015.
  • [2] F. Shahzad, "State-of-the-art Survey on Cloud Computing Security Challenges, Approaches and Solutions", The 6th International Symposium on Applications of Ad hoc and Sensor Networks, PP. 357 –362, 2014.
  • [3] https://www.nist.gov/
  • [4] R.A. Dhote, S. P. Deshpande, "Data Mining with Cloud Computing: -An Overview", International Journal of Advanced Research in Computer Engineering & Technology, Volume 5, Issue 1, January 2016.
  • [5] H. Ahmed, "Data Mining in Cloud Computing", International Journal of Scientific & Engineering Research, Volume 6, Issue 1, January-2015.
  • [6] A. Prasanth, "Cloud Computing Services: A Survey", International Journal of Computer Applications, Volume 46-No.3, May 2012.
  • [7] Q. Zhang, L. Cheng and R. Boutaba, "Cloud Computing: state-of-the-art and research challenges", Journal of Internet Services and Applications, Volume 1, Issue1, pp 7–18, April 2010.
  • [8] X. Geng, Z. Yang, "Data Mining in Cloud Computing", Atlantis Press, 2013.
  • [9] J. ZENG, "The development and application of Data Mining based on Cloud Computing", First International Conference on Advanced Algorithms and Control Engineering, 2018.
  • [10] B. Kaur,"Software As A Service: A Brief Study", International Research Journal of Engineering and Technology, Volume: 02, Issue: 03, June-2015.
  • [11] H. I. Syed and N. A. Baig, "Survey On Cloud Computing", International Journal of Emerging Technology and Advanced Engineering, Volume 3, Issue 4, April 2013.
  • [12] D. Jagli and A. Gupta, "Clustering Model for Evaluating SaaS on the Cloud", International Journal of Application or Innovation in Engineering & Management, Volume 2, Issue 12, December 2013.
  • [13] M.H. Parekh, "Enhancement Clustering of Cloud Datasets using Improved Agglomerative Technique", International Journal of Advanced Networking Applications, 2014.
  • [14] T.C. Sandanayake and P.G.C.Jayangani, "Current Trends in Software as a Service (SaaS)", International Journal for Innovation Education and Research, Volume: 6, No-02, pp.221-234, 2018.
  • [15] R.A. Kautkar, "A Comprehensive Survey on Data Mining", International Journal of Research in Engineering and Technology, Volume: 03, Issue: 08, August-2014.
  • [16] N. Jain and V. Srivastava, "Data Mining Techniques: A Survey Paper", International Journal of Research in Engineering and Technology, Volume: 02, Issue: 11, 2014.
  • [17] www.gartner.com
  • [18] B. Ambulkar and V. Borkar, "Data Mining in Cloud Computing", International Journal of Computer Applications, 2012.
  • [19] S. Mukherjee, R. Shaw, N. Haldar and S. Changdar, "A Survey of Data Mining Applications and Techniques", International Journal of Computer Science and Information Technologies, Vol. 6, PP.4663-4666, 2015.
  • [20] A.Sharma, R. Sharma,V.K. Sharma and V. Shrivatava, "Application of Data Mining -A Survey Paper", International Journal of Computer Science and Information Technologies, Vol. 5, PP.2023-2025, 2014.
  • [21] C. Mehta, "Basics of Data Mining: A Survey Paper", International Journal of Trend in Research and Development, Volume 4, 2017.
  • [22] A. Karahoca, D. Karahoca and M. Şanver, "Survey of Data Mining and Applications (Review from 1996 to Now)", 2012.
  • [23] https://machinelearningmastery.com/classification-versus-regression-in-machine-learning/
  • [24] R. Kabilan and N. Jayaveeran, "Survay of Data Mining Techniques in Cloud Computing", International Journal of Scientific Engineering and Applied Science -Volume-1, Issue-8, November 2015.
  • [25] R.Ş. PETRE, "Data Mining in Cloud Computing", Database Systems Journal, volume 3, 2012.
  • [26] R. Ying, L. Hong, L. Hua-wei, Z. Li-jun and W. Li-na, " Data Mining Based on Cloud-Computing Technology", MATEC Web of Conferences, January 2016.
  • [27] C. Kaushal, A. Arya and S. Pathania, "Integration of Data Mining in Cloud Computing", Advances in Computer Science and Information Technology, Volume 2, Number 7, pp 48 –52, 2015.
  • [28] D. Talia and P. Trunfio, "How Distributed Data Mining Tasks can Thrive as Knowledge Services", Communications of the ACM, vol. 53, n. 7, pp. 132-137, July 2010 Tabii, işte referansları düzeltilmiş hali, aralarında boşluk bırakarak ve numaraları `[ ]` kullanarak sıralanmış şekli:
  • [29] U.S. Patki, "Clustering Algorithms in Cloud Computing Environment", International Research Journal of Computer Science, Volume 4, Issue 04, April 2017.
  • [30] A. Aparajita, S. Swagatika and D. Singh, "Comparative Analysis of Clustering Techniques in Cloud For Effective Load Balancing", International Journal of Engineering and Technology, pp. 47-51, 2018.
  • [31] P. Madhuri and I.K. Rajani, "Improve Performance of clustering on Cloud Datasets using improved Agglomerative CURE Hierarchical Algorithm", International Journal of Science, Engineering and Technology Research, Volume 4, Issue 6, June 2015.
  • [32] K. Srivastava, R. Shah, D. Valia, and H. Swaminarayan, "Data Mining Using Hierarchical Agglomerative Clustering Algorithm in Distributed Cloud Computing Environment", International Journal of Computer Theory and Engineering, Vol. 5, No. 3, June 2013.
  • [33] M. Shindler, A. Wong, "Fast and Accurate k-Means For Large Datasets", 2011.
  • [34] A. Mahendiran, N. Saravanan, N. Venkata Subramanian and N. Sairam, "Implementation of K-Means Clustering in Cloud Computing Environment", Research Journal of Applied Sciences, Engineering and Technology, PP.1391-1394, 2012.
  • [35] R.Atan, "Service Availability and Accessibility of Requirements Using Clustering in Cloud Environment", International Journal on New Computer Architectures and Their Applications, Volume 6, Issue 2, PP. 457-463, 2012.
  • [36] E. Sarkar, C.H. Sekhar, "Organizing Data in Cloud using Clustering Approach", International Journal of Scientific & Engineering Research, Volume 5, Issue 5, May-2014.
  • [37] R. Asnani, "A distributed k-mean clustering algorithm for Cloud Data Mining", International Journal of Engineering Trends and Technology, Volume 30, 2015.
  • [38] B. Panchal and R.K.Kapoor, "Performance Enhancement of Cloud Computing using Clustering", International Journal of Computer Science and Network Security, Volume 14, June 2014.
  • [39] R.S. Sajjan and R.Y. Biradar, "Load Balancing using Cluster and Heuristic Algorithms in Cloud Domain", Indian Journal of Science and Technology, Vol 11, April 2018.
  • [40] Y.H.P. Raju and N. Devarakonda, "Cluster based Hybrid Approach to Task Scheduling in Cloud Environment", International Journal of Advanced Computer Science and Applications, Vol. 10, No. 4, 2019.
  • [41] R. M. Esteves, R. Pais and C. Rong, "K-means Clustering in the Cloud -A Mahout Test", IEEE Workshops of International Conference on Advanced Information Networking and Applications, Singapore, 2011, pp. 514-519. Tabii, işte referansları düzeltilmiş hali, aralarında boşluk bırakarak ve numaraları `[ ]` kullanarak sıralanmış şekli:
  • [42] S. Liu and Y. Cheng, "Research on K-Means Algorithm Based on Cloud Computing," 2012 International Conference on Computer Science and Service System, Nanjing, 2012, pp. 1762-1765.
  • [43] Cui, X., Zhu, P., Yang, X. et al. Optimized big data K-means clustering using MapReduce. J Supercomput 70, 1249–1259 (2014).
  • [44] Yang, X., & Liu, P. A New Algorithm Of The Data Mining Model In Cloud Computing Based On Web Fuzzy Clustering Analysis, Journal of Theoretical and Applied Information Technology, Vol. 49 No.1, March 2013.
  • [45] M. Arjmand and F. Adibnia, "A Fuzzy KNN Classifier for Confidentiality of Cloud Tasks", International Journal of Humanities and Cultural Studies, 2016.
  • [46] J. Wang, "A Novel K-NN Classification Algorithm for Privacy Preserving in Cloud Computing", Research Journal of Applied Sciences, Engineering and Technology, PP. 4865-4870, 2012.
  • [47] P. Bajare, M. Bhoyate, Y. Bhujbal, E. Monika and V. Shinde, "k-Nearest Neighbor Classification Over Encrypted Cloud Data", Journal of Computer Engineering, PP. 45-48, 2015.
  • [48] V. Goutham, P. A. Reddy and K. Sunitha, "K-Nearest Neighbor Classification on Data Confidentiality and Privacy of User’s Input Queries", International Journal of Advanced Research in Computer and Communication Engineering, Vol. 5, Issue 7, July 2016.
  • [49] R. Kour, S. Koul and M. kour, "A Classification Based Approach For Data Confidentiality in Cloud Environment", International Conference on Next Generation Computing and Information Systems, 2017.
  • [50] K. Patel and R. Srivastava, "Classification of Cloud Data using Bayesian Classification", International Journal of Science and Research, Volume 2, Issue 6, June 2013.
  • [51] F. Ebadifard and S.M. Babamir, "Dynamic task scheduling in Cloud Computing based on Naïve Bayesian classifier", International Conference on Information Technology, 2017.
  • [52] L. Zhou, H. Wang and W. Wang, "Parallel Implementation of Classification Algorithms Based on Cloud Computing Environment", TELKOMNIKA Indonesian Journal of Electrical Engineering, Vol.10, pp. 1087-1092, September 2012.
  • [53] He Q., Zhuang F., Li J., Shi Z, "Parallel Implementation of Classification Algorithms Based on MapReduce". In: Yu J., Greco S., Lingras P., Wang G., Skowron A. Rough Set and Knowledge Technology. RSKT 2010. Lecture Notes in Computer Science, vol 6401. Springer, Berlin, Heidelberg.
  • [54] A.B. Kamdar and J.M. Jagani, "A survey: classification of huge Cloud Datasets with efficient Map -Reduce policy", International Journal of Engineering Trends and Technology, Volume 18, 2014.
  • [55] F.O. Catak and M.E. Balaban, "CloudSVM: Training an SVM Classifier in Cloud Computing Systems", ICPCA/SWS, 2013.
  • [56] L.Shuhong, "Improved SVM in Cloud Computing Information Mining", International Journal of Grid Distribution Computing, Volume 8, pp.33-40, 2015.
  • [57] P. Kumar and A. Verma, "Scheduling Using Improved Genetic Algorithm in Cloud Computing for Independent Tasks", International Conference on Advances in Computing, Communications and Informatics, 2012.
  • [58] K. Zhu, H. Song, L. Liu, J. Gao and G. Cheng, "Hybrid Genetic Algorithm for Cloud Computing Applications", IEEE Asia-Pacific Services Computing Conference, Jeju, Korea (South), 2011.
  • [59] T.D. Le, V. Kantere and L. d’ Orazio, "An efficient multi-objective genetic algorithm for Cloud Computing: NSGA-G", IEEE International Conference on Big Data (Big Data), Seattle, WA, USA, pp. 3883-3888, 2018.
  • [60] Z.Lijuanand Z.Shuguang, "The Strategy of Classification Mining Based on Cloud Computing", 1st International Workshop on Cloud Computing and Information Security, 2013.
  • [61] R. Latif, H. Abbas, S. Latif and A. Masood, "EVFDT: An Enhanced Very Fast Decision Tree Algorithm for Detecting Distributed Denial of Service Attack in Cloud-Assisted Wireless Body Area Network", Mobile Information Systems,2015.
  • [62] V. Kanagalakshmi V and R. Gnanaselvam, "Review of Clustering Technique using SaaS on the Cloud", International Journal of Scientific Research in Computer Science, Engineering and Information Technology, Volume 2, Issue 4, 2017.
  • [63] D. Jagli, S. Mahajan and N. S. Chandra, “CBC Approach for Evaluating Potential SaaS on the Cloud”, International Technological Conference (I-TechCON), 2014.
  • [64] D. Jagli, S. Mahajan and N. S. Chandra, "Comparative Clustering Approach Intended for Evaluating SaaS", in International Journal of Computer Applications, Volume 169 –No.8, July 2017.
  • [65] D. Jagli, S. Mahajan and N. S. Chandra, "Implementation of Pam Cluster for Evaluating SaaS on the Cloud Computing Environment", Journal of Engineering, Vol. 08, Issue 4, PP 84-88, April 2018.
  • [66] R. Kamalraj, A.R. Kannan, S.Vaishnavi and V. Suganya, "A DataMining Based Approach for Introducing Products in SaaS (Software as a Service)", International Journal of Engineering Innovation & Research, Volume 1, Issue 2, 2012.
  • [67] D.Jagli, S. Purohit and N.S. Chandra, "EM Clustering Model for Evaluating SaaS on Cloud Computing Environment", Journal of Computer Engineering, Volume 20, Issue 2, PP 67-72, 2018.
  • [68] D.Jagli, S. Purohit and N.S. Chandra, "SAASQUAL: A Quality Model for Evaluating SaaS on the CloudComputing Environment", In Big Data Analytics, pp. 429-437. Springer, Singapore, 2018.
  • [69] Z. I. M. Yusoh and M. Tang, "A Penalty-based Genetic Algorithm for the Composite SaaS Placement Problem in the Cloud", IEEE World Congress on Computational Intelligence, Barcelona, pp. 1-8, July 2010.
  • [70]Z. I. M. Yusoh and M. Tang, "Clustering composite SaaS components in Cloud Computing using a Grouping Genetic Algorithm,"IEEE Congress on Evolutionary Computation, Brisbane, QLD, pp. 1-8, 2012.
  • [71]Z. I. M. Yusoh and M. Tang, "A penalty-based grouping genetic algorithm for multiple composite SaaS components clustering in Cloud,"2012 IEEE International Conference on Systems, Man, and Cybernetics (SMC), Seoul, pp. 1396-1401, 2012.
Yıl 2020, Cilt: 3 Sayı: 1, 23 - 35, 22.12.2020

Öz

Kaynakça

  • Tabii, işte referansları aralarında boşluk bırakarak ve numaraları `[ ]` kullanarak sıralanmış versiyon:
  • [1] S. Bandela, R. Gadde and S. Pabboju, "Survey on Cloud Computing Technologies and Security Threats", International journal of engineering research and technology, Volume 2, Issue 6, May 2015.
  • [2] F. Shahzad, "State-of-the-art Survey on Cloud Computing Security Challenges, Approaches and Solutions", The 6th International Symposium on Applications of Ad hoc and Sensor Networks, PP. 357 –362, 2014.
  • [3] https://www.nist.gov/
  • [4] R.A. Dhote, S. P. Deshpande, "Data Mining with Cloud Computing: -An Overview", International Journal of Advanced Research in Computer Engineering & Technology, Volume 5, Issue 1, January 2016.
  • [5] H. Ahmed, "Data Mining in Cloud Computing", International Journal of Scientific & Engineering Research, Volume 6, Issue 1, January-2015.
  • [6] A. Prasanth, "Cloud Computing Services: A Survey", International Journal of Computer Applications, Volume 46-No.3, May 2012.
  • [7] Q. Zhang, L. Cheng and R. Boutaba, "Cloud Computing: state-of-the-art and research challenges", Journal of Internet Services and Applications, Volume 1, Issue1, pp 7–18, April 2010.
  • [8] X. Geng, Z. Yang, "Data Mining in Cloud Computing", Atlantis Press, 2013.
  • [9] J. ZENG, "The development and application of Data Mining based on Cloud Computing", First International Conference on Advanced Algorithms and Control Engineering, 2018.
  • [10] B. Kaur,"Software As A Service: A Brief Study", International Research Journal of Engineering and Technology, Volume: 02, Issue: 03, June-2015.
  • [11] H. I. Syed and N. A. Baig, "Survey On Cloud Computing", International Journal of Emerging Technology and Advanced Engineering, Volume 3, Issue 4, April 2013.
  • [12] D. Jagli and A. Gupta, "Clustering Model for Evaluating SaaS on the Cloud", International Journal of Application or Innovation in Engineering & Management, Volume 2, Issue 12, December 2013.
  • [13] M.H. Parekh, "Enhancement Clustering of Cloud Datasets using Improved Agglomerative Technique", International Journal of Advanced Networking Applications, 2014.
  • [14] T.C. Sandanayake and P.G.C.Jayangani, "Current Trends in Software as a Service (SaaS)", International Journal for Innovation Education and Research, Volume: 6, No-02, pp.221-234, 2018.
  • [15] R.A. Kautkar, "A Comprehensive Survey on Data Mining", International Journal of Research in Engineering and Technology, Volume: 03, Issue: 08, August-2014.
  • [16] N. Jain and V. Srivastava, "Data Mining Techniques: A Survey Paper", International Journal of Research in Engineering and Technology, Volume: 02, Issue: 11, 2014.
  • [17] www.gartner.com
  • [18] B. Ambulkar and V. Borkar, "Data Mining in Cloud Computing", International Journal of Computer Applications, 2012.
  • [19] S. Mukherjee, R. Shaw, N. Haldar and S. Changdar, "A Survey of Data Mining Applications and Techniques", International Journal of Computer Science and Information Technologies, Vol. 6, PP.4663-4666, 2015.
  • [20] A.Sharma, R. Sharma,V.K. Sharma and V. Shrivatava, "Application of Data Mining -A Survey Paper", International Journal of Computer Science and Information Technologies, Vol. 5, PP.2023-2025, 2014.
  • [21] C. Mehta, "Basics of Data Mining: A Survey Paper", International Journal of Trend in Research and Development, Volume 4, 2017.
  • [22] A. Karahoca, D. Karahoca and M. Şanver, "Survey of Data Mining and Applications (Review from 1996 to Now)", 2012.
  • [23] https://machinelearningmastery.com/classification-versus-regression-in-machine-learning/
  • [24] R. Kabilan and N. Jayaveeran, "Survay of Data Mining Techniques in Cloud Computing", International Journal of Scientific Engineering and Applied Science -Volume-1, Issue-8, November 2015.
  • [25] R.Ş. PETRE, "Data Mining in Cloud Computing", Database Systems Journal, volume 3, 2012.
  • [26] R. Ying, L. Hong, L. Hua-wei, Z. Li-jun and W. Li-na, " Data Mining Based on Cloud-Computing Technology", MATEC Web of Conferences, January 2016.
  • [27] C. Kaushal, A. Arya and S. Pathania, "Integration of Data Mining in Cloud Computing", Advances in Computer Science and Information Technology, Volume 2, Number 7, pp 48 –52, 2015.
  • [28] D. Talia and P. Trunfio, "How Distributed Data Mining Tasks can Thrive as Knowledge Services", Communications of the ACM, vol. 53, n. 7, pp. 132-137, July 2010 Tabii, işte referansları düzeltilmiş hali, aralarında boşluk bırakarak ve numaraları `[ ]` kullanarak sıralanmış şekli:
  • [29] U.S. Patki, "Clustering Algorithms in Cloud Computing Environment", International Research Journal of Computer Science, Volume 4, Issue 04, April 2017.
  • [30] A. Aparajita, S. Swagatika and D. Singh, "Comparative Analysis of Clustering Techniques in Cloud For Effective Load Balancing", International Journal of Engineering and Technology, pp. 47-51, 2018.
  • [31] P. Madhuri and I.K. Rajani, "Improve Performance of clustering on Cloud Datasets using improved Agglomerative CURE Hierarchical Algorithm", International Journal of Science, Engineering and Technology Research, Volume 4, Issue 6, June 2015.
  • [32] K. Srivastava, R. Shah, D. Valia, and H. Swaminarayan, "Data Mining Using Hierarchical Agglomerative Clustering Algorithm in Distributed Cloud Computing Environment", International Journal of Computer Theory and Engineering, Vol. 5, No. 3, June 2013.
  • [33] M. Shindler, A. Wong, "Fast and Accurate k-Means For Large Datasets", 2011.
  • [34] A. Mahendiran, N. Saravanan, N. Venkata Subramanian and N. Sairam, "Implementation of K-Means Clustering in Cloud Computing Environment", Research Journal of Applied Sciences, Engineering and Technology, PP.1391-1394, 2012.
  • [35] R.Atan, "Service Availability and Accessibility of Requirements Using Clustering in Cloud Environment", International Journal on New Computer Architectures and Their Applications, Volume 6, Issue 2, PP. 457-463, 2012.
  • [36] E. Sarkar, C.H. Sekhar, "Organizing Data in Cloud using Clustering Approach", International Journal of Scientific & Engineering Research, Volume 5, Issue 5, May-2014.
  • [37] R. Asnani, "A distributed k-mean clustering algorithm for Cloud Data Mining", International Journal of Engineering Trends and Technology, Volume 30, 2015.
  • [38] B. Panchal and R.K.Kapoor, "Performance Enhancement of Cloud Computing using Clustering", International Journal of Computer Science and Network Security, Volume 14, June 2014.
  • [39] R.S. Sajjan and R.Y. Biradar, "Load Balancing using Cluster and Heuristic Algorithms in Cloud Domain", Indian Journal of Science and Technology, Vol 11, April 2018.
  • [40] Y.H.P. Raju and N. Devarakonda, "Cluster based Hybrid Approach to Task Scheduling in Cloud Environment", International Journal of Advanced Computer Science and Applications, Vol. 10, No. 4, 2019.
  • [41] R. M. Esteves, R. Pais and C. Rong, "K-means Clustering in the Cloud -A Mahout Test", IEEE Workshops of International Conference on Advanced Information Networking and Applications, Singapore, 2011, pp. 514-519. Tabii, işte referansları düzeltilmiş hali, aralarında boşluk bırakarak ve numaraları `[ ]` kullanarak sıralanmış şekli:
  • [42] S. Liu and Y. Cheng, "Research on K-Means Algorithm Based on Cloud Computing," 2012 International Conference on Computer Science and Service System, Nanjing, 2012, pp. 1762-1765.
  • [43] Cui, X., Zhu, P., Yang, X. et al. Optimized big data K-means clustering using MapReduce. J Supercomput 70, 1249–1259 (2014).
  • [44] Yang, X., & Liu, P. A New Algorithm Of The Data Mining Model In Cloud Computing Based On Web Fuzzy Clustering Analysis, Journal of Theoretical and Applied Information Technology, Vol. 49 No.1, March 2013.
  • [45] M. Arjmand and F. Adibnia, "A Fuzzy KNN Classifier for Confidentiality of Cloud Tasks", International Journal of Humanities and Cultural Studies, 2016.
  • [46] J. Wang, "A Novel K-NN Classification Algorithm for Privacy Preserving in Cloud Computing", Research Journal of Applied Sciences, Engineering and Technology, PP. 4865-4870, 2012.
  • [47] P. Bajare, M. Bhoyate, Y. Bhujbal, E. Monika and V. Shinde, "k-Nearest Neighbor Classification Over Encrypted Cloud Data", Journal of Computer Engineering, PP. 45-48, 2015.
  • [48] V. Goutham, P. A. Reddy and K. Sunitha, "K-Nearest Neighbor Classification on Data Confidentiality and Privacy of User’s Input Queries", International Journal of Advanced Research in Computer and Communication Engineering, Vol. 5, Issue 7, July 2016.
  • [49] R. Kour, S. Koul and M. kour, "A Classification Based Approach For Data Confidentiality in Cloud Environment", International Conference on Next Generation Computing and Information Systems, 2017.
  • [50] K. Patel and R. Srivastava, "Classification of Cloud Data using Bayesian Classification", International Journal of Science and Research, Volume 2, Issue 6, June 2013.
  • [51] F. Ebadifard and S.M. Babamir, "Dynamic task scheduling in Cloud Computing based on Naïve Bayesian classifier", International Conference on Information Technology, 2017.
  • [52] L. Zhou, H. Wang and W. Wang, "Parallel Implementation of Classification Algorithms Based on Cloud Computing Environment", TELKOMNIKA Indonesian Journal of Electrical Engineering, Vol.10, pp. 1087-1092, September 2012.
  • [53] He Q., Zhuang F., Li J., Shi Z, "Parallel Implementation of Classification Algorithms Based on MapReduce". In: Yu J., Greco S., Lingras P., Wang G., Skowron A. Rough Set and Knowledge Technology. RSKT 2010. Lecture Notes in Computer Science, vol 6401. Springer, Berlin, Heidelberg.
  • [54] A.B. Kamdar and J.M. Jagani, "A survey: classification of huge Cloud Datasets with efficient Map -Reduce policy", International Journal of Engineering Trends and Technology, Volume 18, 2014.
  • [55] F.O. Catak and M.E. Balaban, "CloudSVM: Training an SVM Classifier in Cloud Computing Systems", ICPCA/SWS, 2013.
  • [56] L.Shuhong, "Improved SVM in Cloud Computing Information Mining", International Journal of Grid Distribution Computing, Volume 8, pp.33-40, 2015.
  • [57] P. Kumar and A. Verma, "Scheduling Using Improved Genetic Algorithm in Cloud Computing for Independent Tasks", International Conference on Advances in Computing, Communications and Informatics, 2012.
  • [58] K. Zhu, H. Song, L. Liu, J. Gao and G. Cheng, "Hybrid Genetic Algorithm for Cloud Computing Applications", IEEE Asia-Pacific Services Computing Conference, Jeju, Korea (South), 2011.
  • [59] T.D. Le, V. Kantere and L. d’ Orazio, "An efficient multi-objective genetic algorithm for Cloud Computing: NSGA-G", IEEE International Conference on Big Data (Big Data), Seattle, WA, USA, pp. 3883-3888, 2018.
  • [60] Z.Lijuanand Z.Shuguang, "The Strategy of Classification Mining Based on Cloud Computing", 1st International Workshop on Cloud Computing and Information Security, 2013.
  • [61] R. Latif, H. Abbas, S. Latif and A. Masood, "EVFDT: An Enhanced Very Fast Decision Tree Algorithm for Detecting Distributed Denial of Service Attack in Cloud-Assisted Wireless Body Area Network", Mobile Information Systems,2015.
  • [62] V. Kanagalakshmi V and R. Gnanaselvam, "Review of Clustering Technique using SaaS on the Cloud", International Journal of Scientific Research in Computer Science, Engineering and Information Technology, Volume 2, Issue 4, 2017.
  • [63] D. Jagli, S. Mahajan and N. S. Chandra, “CBC Approach for Evaluating Potential SaaS on the Cloud”, International Technological Conference (I-TechCON), 2014.
  • [64] D. Jagli, S. Mahajan and N. S. Chandra, "Comparative Clustering Approach Intended for Evaluating SaaS", in International Journal of Computer Applications, Volume 169 –No.8, July 2017.
  • [65] D. Jagli, S. Mahajan and N. S. Chandra, "Implementation of Pam Cluster for Evaluating SaaS on the Cloud Computing Environment", Journal of Engineering, Vol. 08, Issue 4, PP 84-88, April 2018.
  • [66] R. Kamalraj, A.R. Kannan, S.Vaishnavi and V. Suganya, "A DataMining Based Approach for Introducing Products in SaaS (Software as a Service)", International Journal of Engineering Innovation & Research, Volume 1, Issue 2, 2012.
  • [67] D.Jagli, S. Purohit and N.S. Chandra, "EM Clustering Model for Evaluating SaaS on Cloud Computing Environment", Journal of Computer Engineering, Volume 20, Issue 2, PP 67-72, 2018.
  • [68] D.Jagli, S. Purohit and N.S. Chandra, "SAASQUAL: A Quality Model for Evaluating SaaS on the CloudComputing Environment", In Big Data Analytics, pp. 429-437. Springer, Singapore, 2018.
  • [69] Z. I. M. Yusoh and M. Tang, "A Penalty-based Genetic Algorithm for the Composite SaaS Placement Problem in the Cloud", IEEE World Congress on Computational Intelligence, Barcelona, pp. 1-8, July 2010.
  • [70]Z. I. M. Yusoh and M. Tang, "Clustering composite SaaS components in Cloud Computing using a Grouping Genetic Algorithm,"IEEE Congress on Evolutionary Computation, Brisbane, QLD, pp. 1-8, 2012.
  • [71]Z. I. M. Yusoh and M. Tang, "A penalty-based grouping genetic algorithm for multiple composite SaaS components clustering in Cloud,"2012 IEEE International Conference on Systems, Man, and Cybernetics (SMC), Seoul, pp. 1396-1401, 2012.
Toplam 72 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Yapay Yaşam ve Karmaşık Uyarlanabilir Sistemler
Bölüm Reviews
Yazarlar

Abir Achache Bu kişi benim

Abdelhalim Baaziz Bu kişi benim

Toufik Sari Bu kişi benim

Yayımlanma Tarihi 22 Aralık 2020
Yayımlandığı Sayı Yıl 2020 Cilt: 3 Sayı: 1

Kaynak Göster

IEEE A. Achache, A. Baaziz, ve T. Sari, “The Impact of Data Mining and SaaS-Cloud Computing: A Review”, International Journal of Data Science and Applications, c. 3, sy. 1, ss. 23–35, 2020.

AI Research and Application Center, Sakarya University of Applied Sciences, Sakarya, Türkiye.