Review of Various Data Storage and Retrieval Method for Cloud Computing

Authors(3) :-Ajeet Mishra, Prof. Umesh Kumar Lilhore, Prof. Nitesh Gupta

Cloud computing is a widely used computing technology by IT world. It is a fast-growing technique, which serves computing resources such as IaaS, PaaS and SaaS to cloud user on “Pay per use” basis. A Cloud user can store their private data over cloud server and can access securely at any time. The User doesn’t have to worry about storage and maintenance of cloud data. This unique data accessibility feature of cloud attract user to utilize cloud services. Due to the high availability of various IT computing resource over cloud, attracts cloud user to utilize its services. Day by day size of data and services are getting increases over the cloud. It is quite challenging job for cloud service provider to maintain the data integrity and privacy of the stored user data. Another challenge is encounter during retrieval of encrypted stored data. Various cryptography methods are used to maintain the data privacy and integrity. Overcloud server data are stored in encrypted form. After placing the data on the cloud, retrieving the same is also a quite tedious job. In order to retrieve the data, several methods are available suggested by various researchers. Most of the existing techniques are limited to handle a single keyword search with its own limitation. To enhance searching in terms of efficiency and fastness, a multi-keyword search technique can be adapted to retrieve a corresponding document from the cloud. This paper proposes a survey on a secure search scheme supporting single-keyword or multi-keyword ranked search over encrypted cloud data.

Authors and Affiliations

Ajeet Mishra
M. Tech. Research Scholar, NRI Institute of Information Science & Technology Bhopal, Madhya Pradesh, India, India
Prof. Umesh Kumar Lilhore
Head PG, NRI Institute of Information Science & Technology Bhopal, Madhya Pradesh, India, India
Prof. Nitesh Gupta
Assistant Professor, NRI Institute of Information Science & Technology Bhopal, Madhya Pradesh, India, India

Cloud computing, data retrieval, Single keyword, Multi keyword and Racked Search.

  1. NIE Qingbin, LI Pinghua,” An Improved Ant Colony Optimization Algorithm for Improving Cloud Resource Utilization”, 2016 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery, IEEE 2016, PP 311-316
  2. Qiang Guo, “Task scheduling based on ant colony optimization in cloud environment”, 2017 5th International Conference on Computer-Aided Design, Manufacturing, Modeling and Simulation (CDMMS 2017), PP 40039 1- 10
  3. Weifeng Sun, Zhenxing Ji, Jianli Sun, Ning Zhang, Yan Hu, “SAACO: A Self-Adaptive Ant Colony Optimization in Cloud Computing”, IEEE 2015, PP 148-153.
  4. Hongyan Cui,1,2 Xiaofei Liu,1 Tao Yu,3 Honggang Zhang,4 Yajun Fang,5 and Zhongguo Xia, “Cloud Service Scheduling Algorithm Research and Optimization”, Hindawi Security and Communication Networks Volume 2017, Article ID 2503153, PP 1-7
  5. Akash Dave, Prof Bhargesh Patel, Prof. Gopi Bhatt,” Load Balancing In Cloud Computing Using Optimization Techniques: A Study”, IEEE 2016, 114-120
  6. Achar R, Thilagam Ps, Soans N, Vikyath Pv, Rao S, Vijeth Am. Load Balancing In Cloud Based On Live Migration Of Virtual Machines. In 2013 Annual IEEE India Conference (Indian) 2013 Dec 13 (Pp. 1-5). IEEE.
  7. Dam S, Mandal G, Dasgupta K, Dutta P. Genetic Algorithm And Gravitational Emulation Based Hybrid Load Balancing Strategy In Cloud Computing. In Computer, Communication, Control and Information Technology (C3it), 2015 Third International
  8. Conference on 2015 Feb 7 (Pp. 1-7). IEEE.
  9. Zhao Y, Huang W. Adaptive Distributed Load Balancing Algorithm Based On Live Migration Of Virtual Machines In Cloud. In Inc, Ims and Idc, 2009. Ncm'09. Fifth International Joint Conference On 2009 Aug 25 (Pp. 170-175). IEEE.
  10. Ashwin Ts, Domanal Sg, Guddeti Rm. A Novel Bio-Inspired Load Balancing Of Virtual Machines In Cloud Environment. In Cloud Computing In Emerging Markets (Ccem), 2014 IEEE International Conference On 2014 Oct 15 (Pp. 1-4). IEEE.
  11. Zhang Z, Zhang X. A Load Balancing Mechanism Based On Ant Colony And Complex Network Theory In Open Cloud Computing Federation. In Industrial Mechatronics And Automation (Lima), 2010 2nd International Conference On 2010 May 30 (Vol. 2, Pp. 240-243). IEEE
  12. Zhu K, Song H, Liu L, Gao J, Cheng G. Hybrid Genetic Algorithm For Cloud Computing Applications. In Services Computing Conference (Apc), 2011 IEEE Asia-Pacific 2011 Dec 12 (Pp. 182-187). IEEE.
  13. Nishant K, Sharma P, Krishna V, Gupta C, Singh Kp, Rastogi R. Load Balancing Of Nodes In Cloud Using Ant Colony Optimization. In Computer Modeling And Simulation (Taksim), 2012 Maksim 14th International Conference On 2012 Mar 28 (Pp.3-8). IEEE.
  14. Yao J, He JH. Load Balancing Strategy Of Cloud Computing Based On Artificial Bee Algorithm. In Computing Technology And Information Management (CCM), 2012 8th International Conference On 2012 Apr 24 (Vol. 1, Pp. 185-189). IEEE.
  15. Aslanzadeh S, Chaczko Z. Load Balancing Optimization In Cloud Computing: Applying Endocrine-Particle Swarm Optimization. In2015 IEEE International Conference On Electro/Information Technology (Eit) 2015 May 21 (Pp. 165- 169). IEEE.
  16. Sun W, Ji Z, Sun J, Zhang N, Hu Y. Saaco: A Self-Adaptive Ant Colony Optimization In Cloud Computing. In,.Big Data And Cloud Computing (Bdcloud), 2015 IEEE Fifth International Conference On 2015 Aug 26 (Pp. 148-153). IEEE.

Publication Details

Published in : Volume 2 | Issue 5 | September-October 2017
Date of Publication : 2017-10-31
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 584-588
Manuscript Number : CSEIT1725117
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

Ajeet Mishra, Prof. Umesh Kumar Lilhore, Prof. Nitesh Gupta, "Review of Various Data Storage and Retrieval Method for Cloud Computing", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 2, Issue 5, pp.584-588, September-October-2017.
Journal URL :

Article Preview