International Journal of Advanced and Applied Sciences

Int. j. adv. appl. sci.

EISSN: 2313-3724

Print ISSN: 2313-626X

Volume 4, Issue 7  (July 2017), Pages:  29-38

Title:  Comprehensive study of multi-resource cloud simulation tools

Author(s):  Jay Ar P. Esparcia *, Monisha Singh


Department of Computer Science, Christ University, Bangalore-560029, India

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This paper aims to explore Cloud simulation tools comprehensively. Specifically, it is to propose which simulator will fit in one’s preferences since each simulator has its purpose. Gathering data from research papers along with the simulation processes of four cloud simulators provides a comprehensive approach for identifying the parameters in percentage, characteristics and important features of each cloud simulator. Utilizing cloud simulation tools during testing and modeling the real cloud datacenters provide a test environment which gives a repeatable and controllable environment promptly. The said tools offer the possibility to determine quickly whether the wise guess is true or false. Possibly, the stakeholder can map according to the algorithm used, and give various workloads, tasks, the number of hosts, and virtual machines. Also, the inexpensive way to study how the real cloud datacenters work brings more flexibility and scalability. Cloud simulation tools should be the primary instrument for any cloud computing testing, modeling, and technique. 

© 2017 The Authors. Published by IASE.

This is an open access article under the CC BY-NC-ND license (

Keywords: Cloud computing, Cloud simulators, Cloud datacenters, Cloudlets, Provisioning policy

Article History: Received 18 January 2017, Received in revised form 22 April 2017, Accepted 27 April 2017

Digital Object Identifier:


Esparcia JAP and Singh M (2017). Comprehensive study of multi-resource cloud simulation tools. International Journal of Advanced and Applied Sciences, 4(7): 29-38


Amipara H (2015). A survey on CloudSim toolkit for implementing Cloud infrastructure. International Journal of Science Technology and Engineering, 1(12): 239-243.
Ashalatha R, Agarkhed J, and Patil S (2016). Analysis of simulation tools in cloud computing. In the International Conference on Wireless Communications, Signal Processing and Networking (WiSPNET), IEEE, Chennai, India: 748-751.
Belalem G and Limam S (2011). An extension and improvement of the CloudSim simulator. International Journal of Digital Information and Wireless Communications (IJDIWC), 1(2): 373-383.
Buyya R, Ranjan R, and Calheiros RN (2009). Modeling and simulation of scalable Cloud computing environments and the CloudSim toolkit: challenges and opportunities. In the International Conference on High-Performance Computing and Simulation (HPCS'09), IEEE, Leipzig, Germany: 1-11.
Calheiros R, Ranjan R, Beloglazov A, De Rose C, and Buyya R (2010). CloudSim: A toolkit for modeling and simulation of cloud computing environments and evaluation of resource provisioning algorithms. Software: Practice and Experience. 41(1): 23-50.
Castane G, Covarrubias A, and Perez J (2011). iCanCloud: Quick installation guide. Group of Computer Architecture and Technology Area, Universidad Carlos III de Madrid, Madrid, Spain. Available online at: /old/icancloud/downloads/iCanCloud_installationGuide.pdf
Doraya D (2015). A review paper on GreenCloud computing-A new form of computing. International Journal of Advanced Research in Computer Science and Software Engineering, 5(7): 1165-1167.
Ettikyala K and Devi YR (2015). A study on Cloud simulation tools. International Journal of Computer Applications, 115(14): 18-21.
Giannakouris K and Smihily M (2014). Cloud computing - statistics on the use by enterprises. Statistics Explained, Eurostat. Available online at:
Humane P and Varshapriya J (2015). Simulation of cloud infrastructure using CloudSim simulator: A practical approach for researchers. In the International Conference on Smart Technologies and Management for Computing, Communication, Controls, Energy and Materials (ICSTM), IEEE Tamil Nadu, India: 207-211.
Kathiravelu P and Veiga L (2014). Concurrent and distributed cloudsim simulations. In the 22nd IEEE International Conference on Modelling, Analysis and Simulation of Computer and Telecommunication Systems, IEEE, Paris, France: 490-493.
Kliazovich D, Bouvry P, Audzevich Y, and Khan SU (2010). GreenCloud: A packet-level simulator of energy-aware cloud computing data centers. In the Global Telecommunications Conference (GLOBECOM'10), IEEE, Miami, USA: 1-5.
Kumar P and Anjandeep KR (2014). An overview and survey of various cloud simulation tools. Journal of Global Research in Computer Science, 5(1): 24-26.
Schill A (2013). FlexCloud: Reliable and secure cloud overlay infrastructures. Technische Universitat Dresden, Dresden, Germany. Available online at: html
Shaikh R and Sasikumar M (2013). Cloud simulation tools: A comparative analysis. In the IJCA Conference on Green Computing and Technology, Foundation of Computer Science, New York, USA, 3: 11-14. Available online at:
Suryateja P (2016). A comparative analysis of Cloud simulators. International Journal of Modern Education and Computer Science (IJMECS), 8(4): 64-71.
Weins K (2016). Cloud Computing Trends: 2016 State of the Cloud Survey. Right Scale, Available online at:
Xu M, Tian W, Wang X, and Xiong Q (2015). FlexCloud: A flexible and extensible simulator for performance evaluation of virtual machine allocation. In the IEEE International Conference on Smart City/SocialCom/SustainCom (SmartCity), IEEE, Chengdu, China: 649-655.