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Energy-Aware Cloud Computing Simulators: A State of the Art Survey

Year 2018, Volume: 6 Issue: 2, 15 - 20, 30.06.2018

Abstract

Cloud computing is an emerging technology that offers pay-per-use IT services around the world. The daily increase in Cloud infrastructures and modern IT demands (such as web applications, scientific, and business) results in large-scale data centers that lead to additional electricity consumption. The high energy consumption causes a high operating cost and involves a large amount of carbon dioxide emissions that are harmful to the atmosphere. Many academic, governmental, and industrial studies show that energy consumed by computers and different communication units in a data center plays a significant role in the increase of data center operating costs. It is difficult to calculate the performance, security problems, and energy consumption in a true Cloud computing infrastructure. Therefore, in recent years, several simulation tools have been introduced to help researchers for the analysis of a Cloud computing environment. Cloud simulators need to perform simulation tests to reduce the various complexities in Cloud computing environments. Some Cloud simulators have been specially created to test the performance of Cloud computing environments. This study presents the comparative analysis of the state-of-the-art energy aware Cloud simulators. For comparison, several characteristics, functions, and models are employed for most famous energy aware Cloud simulators such as Green Cloud, CloudSim, iCanCloud, Cloud Analyst, Network CloudSim, and CloudReport.

References

  • N. Kaur, T. S. Aulakh, and R. S. Ceema, “Comparison of workflow scheduling algorithms in cloud Computing,” IJACSA, vol. 2, no. 10, pp. 81-86, 2011.
  • Z. Wu, X. Liu, Z. Ni, D. Yuan, and Y. Yang, “A market-oriented hierarchical scheduling strategy in cloud workflow systems,” J Supercomput, vol. 63, no. 1, pp. 256- 293, Jan. 2013.
  • J. Huang, “The Workflow Task Scheduling Algorithm Based on the GA Model in the Cloud Computing Environment,” JSW, vol. 9, no. 4, pp. 873-880, April. 2014.
  • Huth, and J. Cebula, “The basics of cloud Computing,” US-CERT, 2011.
  • D. S. Marcon, L. F. Bittencourt, R. Dantas, M. C. Neves, E. R. Madeira, S. Fernandes, and N. L. da Fonseca. (2013, December).Workflow specification and scheduling with security constraints in hybrid clouds (LatinCloud),2013 2nd IEEE Latin American Conference.
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  • M. Jensen, J. Schwenk J. M. Bohli, N. Gruschka, and L. L. Iacono. (2011, July). Security prospects through cloud computing by adopting multiple clouds (CLOUD), IEEE International Conference Cloud Computing.
  • R. Buyya, R. Ranjan, and R. N. Calheiros. (2010, May). Intercloud: Utility-oriented federation of cloud computing environments for scaling of application services, 2010 International Conference.
  • J. Wang, P. Korambath, I. Altintas, J. Davis, and D. Crawl, “Workflow as a service in the cloud: architecture and scheduling algorithms,” Procedia Comput Sci, vol. 29, pp. 546-556, 2014.
  • L. Wu, S. K. Garg, and R. Buyya. (2011, May). Sla-based resource allocation for software as a service provider (saas) in cloud computing environments (CCGrid), 2011 11th IEEE ACM International Symposium Cluster, Cloud and Grid Computing.
  • S. Basishtha, and S. Boruah, “Cloud Computing and Its Security Aspects”.
  • T. Dillon, C. Wu, and E. Chang. (2010, April). Cloud computing: issues and challenges (AINA), 2010 24th IEEE International Conference.
  • D. Agarwal, and S. Jain, “Efficient optimal algorithm of task scheduling in cloud computing environment,” IJCTT, 2014.
  • Weiss, “Computing in the clouds,” Networker, vol. 11, no. 4, pp. 16-25, 2007.
  • R. Buyya, C. S. Yeo, S. Venugopal, J. Broberg, and I. Brandic, “Cloud computing and emerging IT platforms: Vision, hype, and reality for delivering computing as the 5th utility,” FGCS, vol. 25, no. 6, pp. 599-616, 2009.
  • M. Armbrust, A. Fox, R. Griffith, A. D. Joseph, R. Katz, A. Konwinski, and M. Zaharia, (2010). “A view of cloud computing,” Commun. ACM, vol. 53, no. 4, pp. 50-58, 2010.
  • S. Subashini, and V. Kavitha, “A survey on security issues in service delivery models of cloud computing,” JNCA, vol. 34, no. 1, pp. 1-11, 2011.
  • D. Chappell, “Introducing the Azure services platform,” White paper, vol. 34, no. 1, pp. 1-11, Oct. 2011.
  • Hoefer, C. N. & Karagiannis, G. (2010, December). Taxonomy of cloud computing services (GC Wkshps), 2010 IEEE GLOBECOM Workshops.
  • R. N. Calheiros, R. Ranjan, A. Beloglazov, C. A. De Rose, and R. Buyya, “CloudSim: a toolkit for modeling and simulation of cloud computing environments and evaluation of resource provisioning algorithms,” SPE, vol. 41, no. 1, pp. 23-50, 2011.
  • M. A. Yahya, “A Middleware Approach for Secure Data Outsourcing in the Cloud,” M.S. thesis, Dept Comp. Info Sci, Prince Sultan Univ., Riyadh, Saudi Arabia, 2016.
  • M. Malhotra, “Simulation for enhancing the response and processing time of datacenter,” IJCCR, vol. 1, no. 3, 2011.
  • F. Fittkau, S. Frey, and W. Hasselbring. (2012, September). CDOSim: Simulating cloud deployment options for software migration support (MESOCA), 2012 IEEE 6th International Workshop.
  • W. Zhao, Y. Peng, F. Xie, and Z. Dai. (2012, November). Modeling and simulation of cloud computing: A review (APCloudCC), 2012 IEEE Cloud Computing Congress.
  • T. T. Sá, R. N. Calheiros, and D. G. Gomes, “CloudReports: An extensible simulation tool for energy-aware cloud computing environments,” in Cloud Computing: Challenges, limitations, and R & D Solutions, Ist ed. Switzerland: Springer, 2014, pp. 127-142 [online], Available: https://link.springer.com/chapter/10.1007/978-3-319-10530-7_6
  • C. Kim, J. Kim, and W. J. Lee, “Design of simulator for cloud computing infrastructure and service,” IJSH, vol. 8, no. 6, pp. 27-36, 2014.
  • K. Goga, O. Terzo, P. Ruiu, and F. Xhafa. (2014, July). Simulation, Modeling, and Performance Evaluation Tools for Cloud Applications (CISIS), 2014 8th International Conference.
  • A. Ahmed, and A. S. Sabyasachi. (2014, February). Cloud computing simulators: A detailed survey and future direction (IACC), 2014 IEEE International Computing Conference.
  • Núñez, J. L. Vázquez Poletti, A. C. Caminero, G. G. Castañé, J. Carretero, and I. M. Llorente, “iCanCloud: A flexible and scalable cloud infrastructure simulator,” JGC, vol. 10, no. 1, pp. 185-209, 2012.
  • M. A. Sharkh, A. Kanso, A. Shami, P. Öhlén, “Building a cloud on earth: a study of cloud computing data center simulators,” Comput. Netw, vol. 108, pp. 78-96, 2016.
  • E. Shamsinezhad, A. Shahbahrami, A. Hedayati, A. K. Zadeh, and H. Banirostam, “Presentation Methods for Task Migration in Cloud Computing by Combination of Yu Router and Post-Copy,” IJCSI, vol. 10, no. 4, pp. 98-102, 2013.
  • R. Buyya, C. S. Yeo, S. Venugopal, J. Broberg, I. Brandic, “Cloud computing and emerging IT platforms: Vision, hype, and reality for delivering computing as the 5th utility,” FGCS, vol. 25,no. 6, pp. 599-616, 2009.
  • W. Long, L. Yuqing, and X. Qingxin. (2013, December). Using cloudsim to model and simulate cloud computing environment (CIS), 2013 9th International Conference.
  • J. Shetty, M. R. Anala, G. Shobha, “A survey on techniques of secure live migration of virtual machine,” IJCA, vol. 39, no. 12, pp. 34-39, 2012.
  • L. Liu, H. Wang, X. Liu, X. Jin, W. B. He, Q. B. Wang, and Y. Chen. (2009, June). GreenCloud: a new architecture for green data center (ACM), 2009 6th international conference.
  • K. Chandrasekara. (2013, December). Tutorial: Resource Management in Cloud Computing (ACM), 2013 IEEE 6th International Conference.
  • B. Prakash, S. Manjunatha, H. M. Balakrishna, “A Detailed Survey on Various Cloud Computing Simulators,” IJER, pp. 2319-6890, 2016.
  • S. K. Garg, and R. Buyya. (2011, December). Networkcloudsim: Modelling parallel applications in cloud simulations (UCC), 2011 4th IEEE International Conference.
  • B. Wickremasinghe, R. N. Calheiros, and R. Buyya. (2010, April). Cloudanalyst: A cloudsim-based visual modeller for analysing cloud computing environments and applications (AINA), 2010 24th IEEE International Conference.
  • A. Medina, A. Lakhina, I. Matta, and J. Byers. (2001). BRITE: An approach to universal topology generation. In Modeling, Analysis and Simulation of Computer and Telecommunication Systems 2001 9th IEEE International Symposium.
  • J. C. Huet, and I. E. Abbassi. (2013, December). Green cloud computing modeling methodology (UCC), 2013 IEEE/ACM 6th International Conference.
  • M. I. Tariq, and V. Santarcangelo, “Simulator’s Requirements For Modeling and Simulation Of Cloud Environment” 2015.
  • X. Li, X. Jiang, K. Ye, and P. Huang. (2013, June). DartCSim+: Enhanced cloudsim with the power and network models integrated (CLOUD), 2013 IEEE 6th International Conference.
  • R. Benali, H. Teyeb, A. Balma, S. Tata, and N. B. Hadj-Alouane. (2016, June). Evaluation of traffic-aware VM placement policies in distributed Cloud using CloudSim (WETICE), 2016 IEEE 25th International Conference.
  • B. Louis, K. Mitra, S. Saguna, and C. Åhlund. (2015, December). Cloudsimdisk: Energy-aware storage simulation in cloudsim (UCC), 2015 8th IEEE/ACM International Conference.
  • T. Guérout, T. Monteil, G. Da Costa, R. N. Calheiros, R. Buyya, M. Alexandru, “Energy-aware simulation with DVFS,” SMPT, vol. 39, pp. 76-91, 2013.
  • B. Hasselmann, “Investigation of Multi-Resource Cloud Simulators,” 2015.
  • OMNeT, http://omnetpp.org/,[Accessed online Dec 2017].
  • R. Kumar, “Cloud Computing: An Introspection” IJARCCE, vol. 2, no. 11, Nov. 2013.
  • Hussain, A., Aleem, M., Khan, A., Iqbal, M.A., Islam, M.A., “RALBA: a computation-aware load balancing scheduler for cloud computing”, Cluster Computing, pp. 1-14, Mar. 2018
Year 2018, Volume: 6 Issue: 2, 15 - 20, 30.06.2018

Abstract

References

  • N. Kaur, T. S. Aulakh, and R. S. Ceema, “Comparison of workflow scheduling algorithms in cloud Computing,” IJACSA, vol. 2, no. 10, pp. 81-86, 2011.
  • Z. Wu, X. Liu, Z. Ni, D. Yuan, and Y. Yang, “A market-oriented hierarchical scheduling strategy in cloud workflow systems,” J Supercomput, vol. 63, no. 1, pp. 256- 293, Jan. 2013.
  • J. Huang, “The Workflow Task Scheduling Algorithm Based on the GA Model in the Cloud Computing Environment,” JSW, vol. 9, no. 4, pp. 873-880, April. 2014.
  • Huth, and J. Cebula, “The basics of cloud Computing,” US-CERT, 2011.
  • D. S. Marcon, L. F. Bittencourt, R. Dantas, M. C. Neves, E. R. Madeira, S. Fernandes, and N. L. da Fonseca. (2013, December).Workflow specification and scheduling with security constraints in hybrid clouds (LatinCloud),2013 2nd IEEE Latin American Conference.
  • M. A. AlZain, E. Pardede, B. Soh, and J. A. Thom. (2012, January). Cloud computing security: from single to multi-clouds (HICSS), 2012 45th IEEE Hawaii International Conference.
  • M. Jensen, J. Schwenk J. M. Bohli, N. Gruschka, and L. L. Iacono. (2011, July). Security prospects through cloud computing by adopting multiple clouds (CLOUD), IEEE International Conference Cloud Computing.
  • R. Buyya, R. Ranjan, and R. N. Calheiros. (2010, May). Intercloud: Utility-oriented federation of cloud computing environments for scaling of application services, 2010 International Conference.
  • J. Wang, P. Korambath, I. Altintas, J. Davis, and D. Crawl, “Workflow as a service in the cloud: architecture and scheduling algorithms,” Procedia Comput Sci, vol. 29, pp. 546-556, 2014.
  • L. Wu, S. K. Garg, and R. Buyya. (2011, May). Sla-based resource allocation for software as a service provider (saas) in cloud computing environments (CCGrid), 2011 11th IEEE ACM International Symposium Cluster, Cloud and Grid Computing.
  • S. Basishtha, and S. Boruah, “Cloud Computing and Its Security Aspects”.
  • T. Dillon, C. Wu, and E. Chang. (2010, April). Cloud computing: issues and challenges (AINA), 2010 24th IEEE International Conference.
  • D. Agarwal, and S. Jain, “Efficient optimal algorithm of task scheduling in cloud computing environment,” IJCTT, 2014.
  • Weiss, “Computing in the clouds,” Networker, vol. 11, no. 4, pp. 16-25, 2007.
  • R. Buyya, C. S. Yeo, S. Venugopal, J. Broberg, and I. Brandic, “Cloud computing and emerging IT platforms: Vision, hype, and reality for delivering computing as the 5th utility,” FGCS, vol. 25, no. 6, pp. 599-616, 2009.
  • M. Armbrust, A. Fox, R. Griffith, A. D. Joseph, R. Katz, A. Konwinski, and M. Zaharia, (2010). “A view of cloud computing,” Commun. ACM, vol. 53, no. 4, pp. 50-58, 2010.
  • S. Subashini, and V. Kavitha, “A survey on security issues in service delivery models of cloud computing,” JNCA, vol. 34, no. 1, pp. 1-11, 2011.
  • D. Chappell, “Introducing the Azure services platform,” White paper, vol. 34, no. 1, pp. 1-11, Oct. 2011.
  • Hoefer, C. N. & Karagiannis, G. (2010, December). Taxonomy of cloud computing services (GC Wkshps), 2010 IEEE GLOBECOM Workshops.
  • R. N. Calheiros, R. Ranjan, A. Beloglazov, C. A. De Rose, and R. Buyya, “CloudSim: a toolkit for modeling and simulation of cloud computing environments and evaluation of resource provisioning algorithms,” SPE, vol. 41, no. 1, pp. 23-50, 2011.
  • M. A. Yahya, “A Middleware Approach for Secure Data Outsourcing in the Cloud,” M.S. thesis, Dept Comp. Info Sci, Prince Sultan Univ., Riyadh, Saudi Arabia, 2016.
  • M. Malhotra, “Simulation for enhancing the response and processing time of datacenter,” IJCCR, vol. 1, no. 3, 2011.
  • F. Fittkau, S. Frey, and W. Hasselbring. (2012, September). CDOSim: Simulating cloud deployment options for software migration support (MESOCA), 2012 IEEE 6th International Workshop.
  • W. Zhao, Y. Peng, F. Xie, and Z. Dai. (2012, November). Modeling and simulation of cloud computing: A review (APCloudCC), 2012 IEEE Cloud Computing Congress.
  • T. T. Sá, R. N. Calheiros, and D. G. Gomes, “CloudReports: An extensible simulation tool for energy-aware cloud computing environments,” in Cloud Computing: Challenges, limitations, and R & D Solutions, Ist ed. Switzerland: Springer, 2014, pp. 127-142 [online], Available: https://link.springer.com/chapter/10.1007/978-3-319-10530-7_6
  • C. Kim, J. Kim, and W. J. Lee, “Design of simulator for cloud computing infrastructure and service,” IJSH, vol. 8, no. 6, pp. 27-36, 2014.
  • K. Goga, O. Terzo, P. Ruiu, and F. Xhafa. (2014, July). Simulation, Modeling, and Performance Evaluation Tools for Cloud Applications (CISIS), 2014 8th International Conference.
  • A. Ahmed, and A. S. Sabyasachi. (2014, February). Cloud computing simulators: A detailed survey and future direction (IACC), 2014 IEEE International Computing Conference.
  • Núñez, J. L. Vázquez Poletti, A. C. Caminero, G. G. Castañé, J. Carretero, and I. M. Llorente, “iCanCloud: A flexible and scalable cloud infrastructure simulator,” JGC, vol. 10, no. 1, pp. 185-209, 2012.
  • M. A. Sharkh, A. Kanso, A. Shami, P. Öhlén, “Building a cloud on earth: a study of cloud computing data center simulators,” Comput. Netw, vol. 108, pp. 78-96, 2016.
  • E. Shamsinezhad, A. Shahbahrami, A. Hedayati, A. K. Zadeh, and H. Banirostam, “Presentation Methods for Task Migration in Cloud Computing by Combination of Yu Router and Post-Copy,” IJCSI, vol. 10, no. 4, pp. 98-102, 2013.
  • R. Buyya, C. S. Yeo, S. Venugopal, J. Broberg, I. Brandic, “Cloud computing and emerging IT platforms: Vision, hype, and reality for delivering computing as the 5th utility,” FGCS, vol. 25,no. 6, pp. 599-616, 2009.
  • W. Long, L. Yuqing, and X. Qingxin. (2013, December). Using cloudsim to model and simulate cloud computing environment (CIS), 2013 9th International Conference.
  • J. Shetty, M. R. Anala, G. Shobha, “A survey on techniques of secure live migration of virtual machine,” IJCA, vol. 39, no. 12, pp. 34-39, 2012.
  • L. Liu, H. Wang, X. Liu, X. Jin, W. B. He, Q. B. Wang, and Y. Chen. (2009, June). GreenCloud: a new architecture for green data center (ACM), 2009 6th international conference.
  • K. Chandrasekara. (2013, December). Tutorial: Resource Management in Cloud Computing (ACM), 2013 IEEE 6th International Conference.
  • B. Prakash, S. Manjunatha, H. M. Balakrishna, “A Detailed Survey on Various Cloud Computing Simulators,” IJER, pp. 2319-6890, 2016.
  • S. K. Garg, and R. Buyya. (2011, December). Networkcloudsim: Modelling parallel applications in cloud simulations (UCC), 2011 4th IEEE International Conference.
  • B. Wickremasinghe, R. N. Calheiros, and R. Buyya. (2010, April). Cloudanalyst: A cloudsim-based visual modeller for analysing cloud computing environments and applications (AINA), 2010 24th IEEE International Conference.
  • A. Medina, A. Lakhina, I. Matta, and J. Byers. (2001). BRITE: An approach to universal topology generation. In Modeling, Analysis and Simulation of Computer and Telecommunication Systems 2001 9th IEEE International Symposium.
  • J. C. Huet, and I. E. Abbassi. (2013, December). Green cloud computing modeling methodology (UCC), 2013 IEEE/ACM 6th International Conference.
  • M. I. Tariq, and V. Santarcangelo, “Simulator’s Requirements For Modeling and Simulation Of Cloud Environment” 2015.
  • X. Li, X. Jiang, K. Ye, and P. Huang. (2013, June). DartCSim+: Enhanced cloudsim with the power and network models integrated (CLOUD), 2013 IEEE 6th International Conference.
  • R. Benali, H. Teyeb, A. Balma, S. Tata, and N. B. Hadj-Alouane. (2016, June). Evaluation of traffic-aware VM placement policies in distributed Cloud using CloudSim (WETICE), 2016 IEEE 25th International Conference.
  • B. Louis, K. Mitra, S. Saguna, and C. Åhlund. (2015, December). Cloudsimdisk: Energy-aware storage simulation in cloudsim (UCC), 2015 8th IEEE/ACM International Conference.
  • T. Guérout, T. Monteil, G. Da Costa, R. N. Calheiros, R. Buyya, M. Alexandru, “Energy-aware simulation with DVFS,” SMPT, vol. 39, pp. 76-91, 2013.
  • B. Hasselmann, “Investigation of Multi-Resource Cloud Simulators,” 2015.
  • OMNeT, http://omnetpp.org/,[Accessed online Dec 2017].
  • R. Kumar, “Cloud Computing: An Introspection” IJARCCE, vol. 2, no. 11, Nov. 2013.
  • Hussain, A., Aleem, M., Khan, A., Iqbal, M.A., Islam, M.A., “RALBA: a computation-aware load balancing scheduler for cloud computing”, Cluster Computing, pp. 1-14, Mar. 2018
There are 50 citations in total.

Details

Primary Language English
Subjects Engineering
Journal Section Review
Authors

Ammara Sajjad This is me

Aleena Aqdus Khan This is me

Muhammad Aleem 0000-0001-8342-5757

Publication Date June 30, 2018
Published in Issue Year 2018 Volume: 6 Issue: 2

Cite

APA Sajjad, A., Khan, A. A., & Aleem, M. (2018). Energy-Aware Cloud Computing Simulators: A State of the Art Survey. International Journal of Applied Mathematics Electronics and Computers, 6(2), 15-20.
AMA Sajjad A, Khan AA, Aleem M. Energy-Aware Cloud Computing Simulators: A State of the Art Survey. International Journal of Applied Mathematics Electronics and Computers. June 2018;6(2):15-20.
Chicago Sajjad, Ammara, Aleena Aqdus Khan, and Muhammad Aleem. “Energy-Aware Cloud Computing Simulators: A State of the Art Survey”. International Journal of Applied Mathematics Electronics and Computers 6, no. 2 (June 2018): 15-20.
EndNote Sajjad A, Khan AA, Aleem M (June 1, 2018) Energy-Aware Cloud Computing Simulators: A State of the Art Survey. International Journal of Applied Mathematics Electronics and Computers 6 2 15–20.
IEEE A. Sajjad, A. A. Khan, and M. Aleem, “Energy-Aware Cloud Computing Simulators: A State of the Art Survey”, International Journal of Applied Mathematics Electronics and Computers, vol. 6, no. 2, pp. 15–20, 2018.
ISNAD Sajjad, Ammara et al. “Energy-Aware Cloud Computing Simulators: A State of the Art Survey”. International Journal of Applied Mathematics Electronics and Computers 6/2 (June 2018), 15-20.
JAMA Sajjad A, Khan AA, Aleem M. Energy-Aware Cloud Computing Simulators: A State of the Art Survey. International Journal of Applied Mathematics Electronics and Computers. 2018;6:15–20.
MLA Sajjad, Ammara et al. “Energy-Aware Cloud Computing Simulators: A State of the Art Survey”. International Journal of Applied Mathematics Electronics and Computers, vol. 6, no. 2, 2018, pp. 15-20.
Vancouver Sajjad A, Khan AA, Aleem M. Energy-Aware Cloud Computing Simulators: A State of the Art Survey. International Journal of Applied Mathematics Electronics and Computers. 2018;6(2):15-20.