Full Paper View Go Back

Survey on Minimizing Payment Cost of Multiple Cloud Service Provider

Daimi Aafiya1

Section:Survey Paper, Product Type: Isroset-Journal
Vol.7 , Issue.4 , pp.1-5, Aug-2019


CrossRef-DOI:   https://doi.org/10.26438/ijsrcse/v7i4.15


Online published on Aug 31, 2019


Copyright © Daimi Aafiya . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
 

View this paper at   Google Scholar | DPI Digital Library


XML View     PDF Download

How to Cite this Paper

  • IEEE Citation
  • MLA Citation
  • APA Citation
  • BibTex Citation
  • RIS Citation

IEEE Style Citation: Daimi Aafiya, “Survey on Minimizing Payment Cost of Multiple Cloud Service Provider,” International Journal of Scientific Research in Computer Science and Engineering, Vol.7, Issue.4, pp.1-5, 2019.

MLA Style Citation: Daimi Aafiya "Survey on Minimizing Payment Cost of Multiple Cloud Service Provider." International Journal of Scientific Research in Computer Science and Engineering 7.4 (2019): 1-5.

APA Style Citation: Daimi Aafiya, (2019). Survey on Minimizing Payment Cost of Multiple Cloud Service Provider. International Journal of Scientific Research in Computer Science and Engineering, 7(4), 1-5.

BibTex Style Citation:
@article{Aafiya_2019,
author = {Daimi Aafiya},
title = {Survey on Minimizing Payment Cost of Multiple Cloud Service Provider},
journal = {International Journal of Scientific Research in Computer Science and Engineering},
issue_date = {8 2019},
volume = {7},
Issue = {4},
month = {8},
year = {2019},
issn = {2347-2693},
pages = {1-5},
url = {https://www.isroset.org/journal/IJSRCSE/full_paper_view.php?paper_id=1404},
doi = {https://doi.org/10.26438/ijcse/v7i4.15}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v7i4.15}
UR - https://www.isroset.org/journal/IJSRCSE/full_paper_view.php?paper_id=1404
TI - Survey on Minimizing Payment Cost of Multiple Cloud Service Provider
T2 - International Journal of Scientific Research in Computer Science and Engineering
AU - Daimi Aafiya
PY - 2019
DA - 2019/08/31
PB - IJCSE, Indore, INDIA
SP - 1-5
IS - 4
VL - 7
SN - 2347-2693
ER -

293 Views    305 Downloads    94 Downloads
  
  

Abstract :
Many industries and research center using a cloud service provider (CSP) provider for storing data on that and CSP used many web applications such as web portal, online social network providing services to the clients all over the world. These types of datacenters provide the different unit prices and get/put latencies for resources reservation and allocations. Selection of different CSPs datacenters and cloud customers facing two challenges (I.) How to allocating data to the datacenters in worldwide to satisfy application Service Level Objectives (SLO) requirement which includes both data availability and retrieval latency. (II.) How to allocate reserve resources and data in the datacenters, which belongs to different CSP to minimizing payment cost.Find out the solution of these challenges firstly we used integer programming techniques for handles cost minimization problems. We propose three techniques for reducing the service latency and payment cost 1. Multicast Based Data Transferring, 2. Coefficient Based Data Reallocation and 3. Request Redirection Based Congestion.

Key-Words / Index Term :
Cloud Service Provider, Service Level Objectives, Payment Cost Minimization, and Data Availability

References :
[1]. Z. Wu, M. Butkiewicz, D. Perkins, E. Katz-Bassett, and
H. V. Madhyastha, “SPANStore: Cost-effective geo-replicated storagespanning multiple cloud services,” in Proc. SOSP, Nov. 2013,pp. 292–308.
[2]. G. A. Alvarez et al., “Minerva: An automated resource provisioning toolfor large-scale storage systems,” ACM Trans. Comput. Syst., vol. 19,no. 4, pp. 483–518, Nov. 2001.
[3]. S. Agarwal et al., “Volley: Automated data placement for geo-distributecloud services,” in Proc. NSDI, 2010, p. 28
[4]. R. Kotla, L. Alvisi, and M. Dahlin, “SafeStore: A durable and practicalstorage system,” in Proc. ATC, Jun. 2007, pp. 129–142.
[5]. Y. Yao, Haozhou Wang and K. Liu, “On Storing and Retrieving Geospatial Big-Data in Cloud”, SIGSPTIAL International workshop on use of GIS in the emergency management, ACM, 31-October- 2016.
[6]. Christoph Hochreiner, Stefan Schulte and Michael Borkowski, “Predicting cloud resource utilization”, 9th International conference on utility and cloud computing, 6-December-2016.
[7]. S.H. Gary Chan and Zhangyu Chang, “Video management and resource allocation for a large-scale VoD cloud”, Nature Communication, 24 January 2016ACM Transaction on Multimedia Computing Communication Application, Vol. 12, Article 72, September 2016.
[8]. IbrarYaqoob, SameeUllah Khan, S. Mokhtar and A. Gani, “The rise of big data on cloud computing:Review and open research issues, 2015-Elsevier.
[9]. Zhiming Shen, Qin Jia, Weijia Song, “Supercloud: opportunities and challenges.”,SIGOPS Oper. Syst. Rev, Jan-2015.
[10]. Boyang Wang, Jiqiang Liu, Ming Li, and ShuoQiu, “Toward Practical Privacy-Preserving Frequent Itemset Mining on Encrypted Cloud Data”, IEEE Transactions on Cloud Computing, 2017.
[11]. Miguel Correia, AlyssonBessani, and Bruno Quaresma, “DepSky: Dependable and Secure Storage in a Cloud-of-Clouds”, ACM Transaction Storage, November-2017.
[12]. H. Wu, Z. Feng, C. Guo, and Y. Zhang, “ICTCP: Incast congestion control for TCP in data center networks,” in Proc. CoNEXT, Nov. 2010, pp. 1–12. [38] D. Zats, T. D
[13]. A. Hussam, P. Lonnie, and W. Hakim, “RACS: A case for cloud storage diversity,” in Proc. SoCC, Jun. 2010, pp. 229–240.
[14]. E. Anderson et al., “Hippodrome: Running circles around storage administration,” in Proc. FAST, Jan. 2002, pp. 175–188.
[15]. A. Adya et al., “FARSITE: Federated, available, and reliable storage for an incompletely trusted environment,” in Proc. OSDI, Dec. 2002, pp. 1–4.
[16]. G. Liu and H. Shen, “Minimum-cost cloud storage service across multiple cloud providers,” in Proc. ICDCS, Jun. 2016, pp. 129–138.
[17]. D. Zats, T. Das, P. Mohan, D. Borthakur, and R. Katz, “DeTail: Reducing the flow completion time tail in datacenter networks,” in Proc. SIGCOMM, Sep. 2012, pp. 139–150
[18]. D. Niu, B. Li, and S. Zhao, “Quality-assured cloud bandwidth autoscaling for video-on-demand applications,” in Proc. INFOCOM, 2012, pp. 460–468.
[19]. H. Roh, C. Jung, W. Lee, and D. Du, “Resource pricing game in geodistributed clouds,” in Proc. INFOCOM, Apr. 2013, pp. 1519–1527.
[20]. C. Hong, M. Caesar, and P. B. Godfrey, “Finishing flows quickly with preemptive scheduling,” in Proc. SIGCOMM, Sep. 2012, pp. 127–138.
[21]. B. Vamanan, J. Hasan, and T. N. Vijaykumar, “Deadline-aware datacenter TCP (D2TCP),” in Proc. SIGCOMM, Sep. 2012, pp. 115–126.

Authorization Required

 

You do not have rights to view the full text article.
Please contact administration for subscription to Journal or individual article.
Mail us at  support@isroset.org or view contact page for more details.

Go to Navigation