Novel Cloud Architecture to Decrease Problems Related to Big Data

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Author(s)

Entesar Althagafy 1,* M. Rizwan Jameel Qureshi 1

1. Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah, Saudi Arabia

* Corresponding author.

DOI: https://doi.org/10.5815/ijcnis.2017.02.07

Received: 3 Aug. 2016 / Revised: 11 Oct. 2016 / Accepted: 1 Dec. 2016 / Published: 8 Feb. 2017

Index Terms

Cloud Computing, Big Bata Problem, Big Data Infrastructure, AWS, Eucalyptus, Hadoop

Abstract

IT companies are facing many difficulties and challenges when dealing with big data. These difficulties have surfaced due to the ever-expanding amount of data generated via personal computer, mobile devices, and social network sites. The significant increase in big data has created challenges for IT companies that need to extract necessary information and knowledge. Cloud computing, with its virtualized resources usage and dynamic scalability, is broadly used in organizations to address challenges related to big data and has an important influence on business in organizations. Furthermore, big data is changing the way organizations do business. This paper proposes novel cloud architecture to decrease problems related to big data. The proposed architecture is a combination of many big data infrastructures in the creation of a service. This architecture minimizes problems related to big data by improving performance and quality of service.

Cite This Paper

Entesar Althagafy, M. Rizwan Jameel Qureshi, "Novel Cloud Architecture to Decrease Problems Related to Big Data", International Journal of Computer Network and Information Security(IJCNIS), Vol.9, No.2, pp.53-60, 2017. DOI:10.5815/ijcnis.2017.02.07

Reference

[1]Patel A. and Birla M. and Nair U., "Addressing big data problem using Hadoop and Map Reduce," 2012 Nirma University International Conference on Engineering, Gujarat, India, pp. 1-5, 2012.‏
[2]Pothuganti A., "Big Data Analytics: Hadoop-Map Reduce & NoSQL Databases."‬‏
[3]Frantsvog D. and Seymour T. and John F. "Cloud Computing," International Journal of Management & Information Systems (IJMIS), vol. 16, no. 4, pp. 317-324, 2012.
[4]Adnan M., et al., "Minimizing big data problems using cloud computing based on Hadoop architecture," 2014 11th Annual High-capacity Optical Networks and Emerging/Enabling Technologies (HONET), 2014.
[5]Purcell B., "Big data using cloud computing," Holy Family University Journal of Technology Research, 2013.
[6]Padhy R., "Big Data Processing with Hadoop-MapReduce in Cloud Systems," International Journal of Cloud Computing and Services Science (IJ-CLOSER), vol. 2, no. 1, pp. 16-27, 2012.
[7]Ji C., et al., "Big data processing in cloud computing environments," 2012 International Symposium on Pervasive Systems, Algorithms and Networks (I-SPAN), San Marcos, Texas, 2012.
[8]Hao, Chen, and Qiao Ying. "Research of Cloud Computing based on the Hadoop platform." Computational and Information Sciences (ICCIS), 2011 International Conference on. IEEE, 2011.
[9]Ramamoorthy S. and Rajalakshmi S., "Optimized data analysis in cloud using BigData analytics techniques," 2013 Fourth International Conference on Computing, Communications and Networking Technologies (ICCCNT), Tiruchengode, India, pp. 1-5, 2013.
[10]Ye F, et al., "Cloud-Based Big Data Mining & Analyzing Services Platform Integrating R," 2013 International Conference on Advanced Cloud and Big Data (CBD), Nanjing, China, pp. 147-151, 2013.
[11]Zhang J. and Huang M., "5Ws model for Big Data analysis and visualization,", 2013 IEEE 16th International Conference on Computational Science and Engineering (CSE), Sydney, Australia, pp. 1021-1028, 2013.
[12]Gu G., et al., "An overview of newly open-source cloud storage platforms," 2012 IEEE International Conference on Granular Computing (GrC), Hangzhou, China, pp. 142-147, 2012.
[13]Katal A. and Wazid M. and Goudar R., "Big data: Issues, challenges, tools and Good practices," 2013 Sixth International Conference on Contemporary Computing (IC3), Noida, India, pp. 404-409, 2013.
[14]Ahuja S. and Moore B., "State of Big Data Analysis in the Cloud," Network and Communication Technologies, vol. 2, no. 1, pp. p62, 2013.
[15]Shamsi J., Khojaye M., and Qasmi M. "Data-intensive cloud computing: requirements, expectations, challenges, and solutions," Journal of grid computing, vol. 11, no. 2, pp. 281-310, 2013.
[16]Amiry V., et al., "Implementing Hadoop Platform on Eucalyptus Cloud Infrastructure," 2012 Seventh International Conference on P2P, Parallel, Grid, Cloud and Internet Computing (3PGCIC), Victoria, Canada, pp. 74-78, 2012.
[17]Tarannum N., and Ahmed N., "Efficient and Reliable Hybrid Cloud Architecture for big Database," International Journal on Cloud Computing: Services and Architecture (IJCCSA), vol. 3, no. 6, pp. 17-29, 2013.
[18]Jie S. and Yao J. and Wu C., "Cloud computing and its key techniques," 2011 International Conference on Electronic and Mechanical Engineering and Information Technology (EMEIT), Heilongjiang, China, vol. 1, pp. 320-324, 2011.