Call for Paper - September 2020 Edition
IJCA solicits original research papers for the September 2020 Edition. Last date of manuscript submission is August 20, 2020. Read More

Fuzzy based Efficient Service Broker Policy for Cloud

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2017
Nazmul Islam, Sajjad Waheed

Nazmul Islam and Sajjad Waheed. Fuzzy based Efficient Service Broker Policy for Cloud. International Journal of Computer Applications 168(4):37-40, June 2017. BibTeX

	author = {Nazmul Islam and Sajjad Waheed},
	title = {Fuzzy based Efficient Service Broker Policy for Cloud},
	journal = {International Journal of Computer Applications},
	issue_date = {June 2017},
	volume = {168},
	number = {4},
	month = {Jun},
	year = {2017},
	issn = {0975-8887},
	pages = {37-40},
	numpages = {4},
	url = {},
	doi = {10.5120/ijca2017914353},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}


Cloud computing is a type of internet based computing that provides shared computer processing resources, storage and data to computers on user demand. Today’s time, it becomes very popular due to new facilities and technologies. It deals with large amount of data so that it is necessary to simulate the behavior of cloud in real field. So that the simulation tools as like cloud-analyst, cloudsim are commonly used. These simulators are using different load balancing policy and service brokerage strategy. My proposed service brokerage strategy increases the efficiency and minimizes the cost.


  1. Foster, I., et al. Cloud computing and grid computing 360-degree compared. In Grid Computing Environments Workshop, 2008. GCE'08. 2008. IEEE.
  2. Ahmed, M., et al., An advanced survey on cloud computing and state-of-the-art research issues. Int J Comput Sci Issues (IJCSI), 2012. 9.
  3. Dash, M., A. Mahapatra, and N.R. Chakraborty, Cost Effective Selection of Data Center in Cloud Environment. International Journal on Advanced Computer Theory and Engineering (IJACTE), 2013. Volume-2(Issue-1): p. pp 2319 – 2526.
  4. Wickremasinghe, B. and R. Buyya, CloudAnalyst: A CloudSim-based Tool for Modelling and Analysis of Large Scale Cloud Computing Environments. MEDC Project Report, 2009. 22(6).
  5. Bala, M., Performance Evaluation of Large Scaled Applications using Different Load Balancing Tactics in Cloud Computing. International Journal of Computer Applications, 2013. 76(No.14): p. pg 17-22.
  6. Wickremasinghe, B., R.N. Calheiros, and R. Buyya. Cloudanalyst: A cloudsim-based visual modeller for analysing cloud computing environments and applications. in Advanced Information Networking and Applications (AINA), 2010 24th IEEE International Conference on. 2010. IEEE
  7. Zia, A. and M. Khan, A Scheme to Reduce Response Time in Cloud Computing Environment. International Journal of Modern Education & Computer Science, 2013. 5(6).
  8. Dakshayini, R.P.M.a.M., Service Broker Routing Polices in Cloud Environment: A SurveyInternational Journal of Advances in Engineering & Technology (IJAET) 2014. Volume 6(Issue 6): p. pp. 2717-2723.
  9. Calheiros, R.N., et al., CloudSim: a toolkit for modeling and simulation of cloud computing environments and evaluation of resource provisioning algorithms. Software: Practice and Experience, 2011. 41(1): p. 23- 50.
  10. Y. Bai,D. Wang, " Fundamentals of Fuzzy Logic Control – Fuzzy Sets, Fuzzy Rules and Defuzzifications", Journal of advance Fuzzy Logic Technologiesin Industrial Application, 2006, xxv,334p.
  11. A.I Swapna, Md. H Rahman, Md. Akramuzzaman, “Performance Evaluation of Fuzzy Integrated Firewall Model for Hybrid Cloud Based on Packet Utilization", Journal on cloud computing, 2016 IEEE 978-1-4673-8515-2.


Simulation, fuzzy, Service broker policy, cloud computing, cloud-analyst.