Cloud computing is the latest distributed computing paradigm and it offers various opportunities to solve largeamount of scientific problems. Cloud-enabled VM for developers and scientists. Huge data analysis can be done using cloud computing and machine learning technique management for developers & scientists. We are working on the technology framework for weather analytics. Weather science is Big Data domain .Weather plays an important role in everyday life. Weather prediction has been the one of the most challenging issue around the world in last year. Various techniques are used for prediction are Statistical analysis, Data mining, Regression analysis, and neural networks. This paper represents machine learning technique for the early prediction of weather on hadoop in Openstack cloud.

 

Published In : IJCSN Journal Volume 4, Issue 5

Date of Publication : October 2015

Pages : 749 - 752

Figures :02

Tables : 01

Publication Link : Weather Analytics Using Machine Learning Techniques On Openstack Cloud

 

 

 

Pratima Devidas Nerkar : completed B.E. in Computer Engineering in 2011 from K.K.Wagh C.O.E ,Nashik.

Suresh Baliram Rathod : completed B.E. in Information Technology in 2007 from STBCE; Tuljapur.He has also completed his M.E. from SCOE, Pune.

 

 

 

 

 

 

 

Cloud computing

weather analytics

machine learning technique

big data

hadoop

Weather has a great impact on agriculture, economy not only in India but across the whole world In this paper we have proposed a method for weather analytics prediction. This is the only prediction regarding weather but not accurate because of weather factors.

 

 

 

 

 

 

 

 

 

[1] Quyet Thang NGUYEN, Nguyen QUANG-HUNG, Nguyen HUYNH TUONG,Van Hoai TRAN, Nam THOAI ,"Virtual Machine Allocation in Cloud Computing for Minimizing Total Execution Time on Each Machine,"978-1-4673-2088-7,IEEE,2013. [2] Han Chen, Minkyong Kim, Zhe Zhang, Hui Lei, “Empirical Study of Application Runtime Performance using On-demand Streaming Virtual Disks in the Cloud”. [3] “Cloud computing,” http://www.ibm.com/cloudcomputing/ us/en/whatis-cloud computing.html. [4] Zhiming Shen, Zhe Zhang, Andrzej Kochut, Alexei Karve, Han Chen, Minkyong Kim Hui Lei, Nicholas Fuller, “VMAR: Optimizing I/O Performance and Resource Utilization in the Cloud”. [5] K. H. Kim, W. Y. Lee, J. Kim, R. Buyya. “SLA-Based Scheduling of Bag-of- Tasks Applications on Power- Aware Cluster Systems,” IEICE Transactions on Information and Systems, Issue 12, pp. 3194-3201, 2010. [6] P. Padala, “Understanding live migration of virtual machines.” Available: http://tinyurl.com/24bdaza, Jun. 2010. [7] D. Breitgand, G. Kutiel, and D. Raz, “Cost-aware live migration of services in the cloud,” in 2011 USENIX Workshop on Hot Topics in Management of Internet, Cloud, and Enterprise Networks and Services. [8] S.Hacking and B. Hudzia, “Improving the live migration process of large enterprise applications,” inProceedings 2009 International Workshop on Virtualization Technologies in Distributed Computing. [9] A. Beloglazov, R. Buyya. “Energy Efficient Allocation of Virtual Machines in Cloud Data Centers,” 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing, pp. 577-578, 2010. [10] Girish L S, Dr. H S Guruprasad, “Building Private Cloud using OpenStack ,” , International Journal of Emerging Trends & Technology in Computer Science Vol. 3, Issue 3, May – June 2014 , ISSN 2278-6856 [11] SonaliYadav, “Comparative Study on Open Source Software for Cloud Computing Platform: Eucalyptus,Openstack and Opennebula”, International Journal Of Engineering And Science, Vol.3, Issue 10 (October 2013), pp 51-54, ISSN (e): 2278-4721, ISSN (p):2319-6483. [12] Bram Rongen, “Making the case for migration of information systems to the cloud”,16thStudent Conference on IT, Enschede, The Netherlands, Jan 27 2012, Copyright 2011, University of Twente, Faculty of Electrical Engineering, Mathematics and Computer Science. [13] Rashmi,Dr.Shabana,Mehfuz, Dr.G.Sahoo, “A fivephased approach for the cloud migration”,International Journal of Emerging Technology and Advanced Engineering,April 2012, ISSN 2250-2459. [14] A. Beloglazov, J. Abawajy and R. Buyya," Energyaware resource allocation heuristics for e_cient management of data centers for Cloud computing," Future Generation Computer Systems, vol. 28, no. 5, pp. 755-768, 2012. DOI:10.1016/j.future.2011.04.017. [15] Rajkumar Buyya , Andrzej Goscinski ,” CLOUD COMPUTING -Principles and Paradigms ” [16] Carlo Mastroianni, Michela Meo, and Giuseppe Papuzzo,” Probabilistic Consolidation of Virtual Machines in Self-Organizing Cloud Data Centers,” IEEE TRANSACTIONS ON CLOUD COMPUTING, VOL. 1, NO. 2, JULY-DECEMBER 2013 [17] Mladen A. Vouk,” Cloud Computing – Issues, Research and Implementations,” Journal of Computing and Information Technology - CIT 16, 2008, 4, 235– 246 [18] Worachat Chawarut, Lilakiatsakun Woraphon,” Energy-Aware and Real-time Service Management In Cloud Computing,”IEEE,2013 [19] T.Swathi, K.Srikanth, S. Raghunath Reddy,” VIRTUALIZATION IN CLOUD COMPUTING,” IJCSMC, Vol. 3, Issue. 5, May 2014, pg.540 – 546 [20] Neha Khandelwal et.al “ Climatic Assessment Of Rajasthan’s Region For Drought With Concern Of Data Mining Techniques” in International Journal Of Engineering Research and Applications (IJERA) ISSN: 2248-9622 www.ijera.com Vol. 2, Issue 5, September- October 2012, pp.1695-1697. [21] Pratima D.Nerkar ,Prof .Suresh B.Rathod,”A Survey on Performance and Energy Management in cloud computing,”International Journal of Science and Research , , Vol. 3, Issue. 11, 2319-7064 , Nov.2014 [22] Pratima D.Nerkar ,Prof .Suresh B.Rathod ,”A survey on virtualization technology in cloud computing ,”International journal of Advance Research in Science and Engineering , , Vol. 3, Issue. 11, 2319-8354 , Nov.2014.