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Reseach Article

Fairly Scheduled Bandwidth for the Data Centre Traffic

by Manjur Kolhar, Abdalla Alameen
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 166 - Number 5
Year of Publication: 2017
Authors: Manjur Kolhar, Abdalla Alameen
10.5120/ijca2017914102

Manjur Kolhar, Abdalla Alameen . Fairly Scheduled Bandwidth for the Data Centre Traffic. International Journal of Computer Applications. 166, 5 ( May 2017), 38-43. DOI=10.5120/ijca2017914102

@article{ 10.5120/ijca2017914102,
author = { Manjur Kolhar, Abdalla Alameen },
title = { Fairly Scheduled Bandwidth for the Data Centre Traffic },
journal = { International Journal of Computer Applications },
issue_date = { May 2017 },
volume = { 166 },
number = { 5 },
month = { May },
year = { 2017 },
issn = { 0975-8887 },
pages = { 38-43 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume166/number5/27668-2017914102/ },
doi = { 10.5120/ijca2017914102 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:12:55.520702+05:30
%A Manjur Kolhar
%A Abdalla Alameen
%T Fairly Scheduled Bandwidth for the Data Centre Traffic
%J International Journal of Computer Applications
%@ 0975-8887
%V 166
%N 5
%P 38-43
%D 2017
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Maintaining the bandwidth across a data center to meet the service level agreement is a major challenge for network administrators. If the bandwidth is not scheduled according to application requirements, the applications will be executed with increased or decreased provisioning or moved to other data centers. Hence, we developed a bandwidth scheduling algorithm that operates according to application requirements and partitions the available bandwidth to accommodate the available traffic. We simulated this algorithm with the SimPy tool and found that the proposed algorithm performs better than the general allocation and partition schemes.

References
  1. Divakaran DM, Hegde S, Srinivas R, Gurusamy M. Dynamic resource allocation in hybrid optical–electrical datacenter networks. Computer Communications. 2015 Sep 15;69:40-9.
  2. Hindman B, Konwinski A, Zaharia M, Ghodsi A, Joseph A, Katz R, Stoica I. Mesos: A platform for fine-grained resource sharing in the data center. In: USENIX 2011 Networked Systems Design and Implementation; 1 April 2011; Boston, Massachusetts, USA: USENIX. pp. 22-22.
  3. Al-Fares M, Loukissas A, Vahdat A. A scalable, commodity data center network architecture. ACM SIGCOMM Computer Communication Review. 2008 Oct 1;38(4):63-74.
  4. Farrington N, Alexey A. Facebook’s data center network architecture. In: IEEE 2013 Interconnects Conference; 5-8 May 2013; Santa Fe, New Mexico: IEEE. pp. 5-7.
  5. Benson T, Akella A, Maltz D. Network traffic characteristics of data centers in the wild. In: ACM 2010 SIGCOMM Internet Measurement; 1-3 November 2010; Melbourne, Australia: ACM. pp. 267-280.
  6. Lee J, Yoshio T, Myungjin L, Lucian P, Sujata B, Joon-Myung K, Puneet S. Application-driven bandwidth guarantees in datacenters. In: ACM 2014 SIGCOMM Conference; 19-21 August 2014; Chicago, Illinois, USA: ACM. pp. 467-478.
  7. Nan G, Zhifei M, Mei Y, Minqiang L, Honggang W, Yan Z. Stackelberg game for bandwidth allocation in cloud-based wireless live-streaming social networks. IEEE Syst J 2014; 1: 256-267.
  8. Ghosh P, Kalyan B, Sajal D. A game theory-based pricing strategy to support single/multiclass job allocation schemes for bandwidth-constrained distributed computing systems. IEEE T Parall Distr 2007; 18: 289-306.
  9. Ye Z, Yong L, Guang S, Depeng J, Li S, Lieguang Z. Game theory based bandwidth allocation scheme for network virtualization. In: IEEE 2010 Global Telecommunications Conference; 7-9 December 2010; Miami, Florida, USA: IEEE. .pp. 1-5.
  10. Di N, Chen F, Baochun L. A theory of cloud bandwidth pricing for video-on-demand providers. In: IEEE 2012 INFOCOM; 25-30 March 2012; Orlando, Florida, USA: IEEE. pp. 711-719.
  11. Kasbekar S, Saswati S. Spectrum pricing games with bandwidth uncertainty and spatial reuse in cognitive radio networks. In: ACM 2010 International Symposium on Mobile Adhoc Networking and Computing; 20-24 September 2010; Chicago, Illinois, USA: ACM.
  12. Guo C, Lu G, Wang HJ, Yang S, Kong C, Sun P, Wu W, Zhang Y. Secondnet: a data center network virtualization architecture with bandwidth guarantees. InProceedings of the 6th International COnference 2010 Nov 30 (p. 15). ACM.
  13. Cao Z, Proietti R, Clements M, Yoo SB. Experimental Demonstration of Flexible Bandwidth Optical Data Center Core Network With All-to-All Interconnectivity. Journal of Lightwave Technology. 2015 Apr 15;33(8):1578-85.
  14. Divakaran DM, Gurusamy M. Towards flexible guarantees in clouds: Adaptive bandwidth allocation and pricing. Parallel and Distributed Systems, IEEE Transactions on. 2015 Jun 1;26(6):1754-64.
  15. Li D, Zhu J, Wu J, Guan J, Zhang Y. Guaranteeing heterogeneous bandwidth demand in multitenant data center networks. Networking, IEEE/ACM Transactions on. 2015 Oct;23(5):1648-60.
  16. Zhang J, Ren F, Yue X, Shu R, Lin C. Sharing bandwidth by allocating switch buffer in data center networks. Selected Areas in Communications, IEEE Journal on. 2014 Jan;32(1):39-51.
  17. Jin H, Pan D, Liu J, Pissinou N. Openflow-based flow-level bandwidth provisioning for cicq switches. IEEE Transactions on Computers. 2013 Sep;62(9):1799-812.
  18. Skoutas DN, Makris P, Skianis C. Optimized admission control scheme for coexisting femtocell, wireless and wireline networks. Telecommunication Systems. 2013 Jul 1;53(3):357-71.
Index Terms

Computer Science
Information Sciences

Keywords

Data center cloud computing bandwidth reservation resource sharing.