CFP last date
20 December 2024
Reseach Article

Performance Analysis of Various Architectural Approaches in Cloud Computing Environment for Energy and Bandwidth Minimization

by N. R. Ram Mohan, E. Baburaj
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 96 - Number 4
Year of Publication: 2014
Authors: N. R. Ram Mohan, E. Baburaj
10.5120/16785-6370

N. R. Ram Mohan, E. Baburaj . Performance Analysis of Various Architectural Approaches in Cloud Computing Environment for Energy and Bandwidth Minimization. International Journal of Computer Applications. 96, 4 ( June 2014), 45-51. DOI=10.5120/16785-6370

@article{ 10.5120/16785-6370,
author = { N. R. Ram Mohan, E. Baburaj },
title = { Performance Analysis of Various Architectural Approaches in Cloud Computing Environment for Energy and Bandwidth Minimization },
journal = { International Journal of Computer Applications },
issue_date = { June 2014 },
volume = { 96 },
number = { 4 },
month = { June },
year = { 2014 },
issn = { 0975-8887 },
pages = { 45-51 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume96/number4/16785-6370/ },
doi = { 10.5120/16785-6370 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:20:54.501540+05:30
%A N. R. Ram Mohan
%A E. Baburaj
%T Performance Analysis of Various Architectural Approaches in Cloud Computing Environment for Energy and Bandwidth Minimization
%J International Journal of Computer Applications
%@ 0975-8887
%V 96
%N 4
%P 45-51
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Cloud Computing is one of the mainly admired subject in the computational world. It is support to processing the data that was emerged by profitable infrastructure. Cloud computing consist of large number of servers comprising of both virtual and physical servers in order to provide the resources in an optimal manner. The evolution of Cloud computing provides customers the illusion of infinite computing resources which are available from anywhere, anytime, on demand. It offers a user the service (called "Infrastructure as a Service" - IaaS) of renting computing resources over the Internet. Some of the important issues related to cloud computing are the cloud rely on large scale infrastructures, consumes maximum bandwidth and high energy consumption to obtain the process. The user can select from different types of computing resources based on the requirements. In this work, we have evaluated several existing cloud computing techniques related on energy and bandwidth consumption. Various Energy conservation strategies and resource allocation strategies and their challenges are discussed for which the results obtained can be benefitted by both researchers and cloud users. The work also evaluates the impact created by the resource while performing scheduling during various aspects, including number of users involved in cloud, types of resources used and the total number of data centers involved while performing the analysis. The result of survey not only measures the similarities and differences of the different architectural approaches presented for cloud users but also to identify areas requiring further research.

References
  1. Anton Beloglazov, Jemal Abawajy, Rajkumar Buyya, "Energy-aware resource allocation heuristics for efficient management of data centers for Cloud computing", Future Generation Computer Systems, pp. 755–768, 2012.
  2. Anusha Reddy, Dr. M. Janga Reddy," Dynamic Resource Allocation and Data Processing Framework for Cloud Architecture" International Journal of Advanced Research in Computer Science and Software Engineering, Volume 2, Issue 10, October 2012
  3. Chandrashekhar S. Pawar and R. B. Wagh," A review of resource allocation policies in cloud computing", Proceedings in World Journal of Science and Technology, 2012
  4. Daniel Warneke and Odej Kao, "Exploiting Dynamic Resource Allocation for Efficient Parallel Data Processing in the Cloud", IEEE Transactions on Parallel and Distributed Systems, January 2011.
  5. Qian Wang, Kui Ren, Wenjing Lou, and Jin Li," Enabling Public Auditability and Data Dynamics for Storage Security in Cloud Computing", IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS, VOL. 22, NO. 5, MAY 2011
  6. Jianhua Gu, Jinhua Hu, Tianhai Zhao, Guofei Sun, "A New Resource Scheduling Strategy Based on Genetic Algorithm in Cloud Computing Environment", Journal Of Computers, vol. 7, no. 1, January 2012.
  7. Jianfeng Yan, Wen-Syan Li,"Calibrating Resource Allocation for Parallel Processing of Analytic Tasks", IEEE International Conference on e-Business Engineering, 2009.
  8. Kumar, K. , Jing Feng, Nimmagadda, Y. , Yung-Hsiang Lu, "Resource Allocation for Real-Time Tasks Using Cloud Computing", IEEE, Computer Communications and Networks (ICCCN), 2011.
  9. Mehta, A. , Menaria, M. , Dangi, S. , Rao, S. , "Energy conservation in cloud infrastructures",IEEE International Conference on Systems Conference (SysCon), 2011.
  10. Olivier Beaumont, Lionel Eyraud-Dubois and Hejer Rejeb," Heterogeneous Resource Allocation under Degree Constraints", IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS
  11. Smitha Sundareswaran, Anna C. Squicciarini, Member, IEEE, and Dan Lin," Ensuring Distributed Accountability for Data Sharing in the Cloud", IEEE TRANSACTIONS ON DEPENDABLE AND SECURE COMPUTING, VOL. 9, NO. 4, AUGUST 2012
  12. Takuro TOMITA and Shin-ichi KURIBAYASHI, "Congestion control method with fair resource allocation for cloud computing environments",IEEE, 2011.
  13. Xindong You, Jian Wan, Xianghua Xu, Congfeng Jiang, Wei Zhang, Jilin Zhang, "ARAS-M: Automatic Resource Allocation Strategy based on Market Mechanism in Cloud Computing", Journal Of Computers, VOL. 6, NO. 7, JULY 2011.
  14. Vivek Nallur, Rami Bahsoon," A Decentralized Self-Adaptation Mechanism For Service-Based Applications in The Cloud", IEEE TRANSACTIONS ON SOFTWARE ENGINEERING
  15. Yan Zhu, Hongxin Hu, Gail-Joon Ahn, Senior Member, IEEE, Mengyang Yu," Cooperative Provable Data Possession for Integrity Verification in Multi-Cloud Storage", IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS, Jun 2012
  16. Younge, A. J. , von Laszewski, G. ; Lizhe Wang ; Lopez-Alarcon, S. ; Carithers, W. , "Efficient resource management for Cloud computing environments", International Green Computing Conference, 2010.
  17. Zhongni Zheng, Rui Wang, Hai Zhong, Xuejie Zhang, "An approach for cloud resource scheduling based on Parallel Genetic Algorithm", IEEE, 2011.
  18. Zhiguo Wan, Jun'e Liu, and Robert H. Deng," HASBE: A Hierarchical Attribute-Based Solution for Flexible and Scalable Access Control in Cloud Computing", IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY, VOL. 7, NO. 2, APRIL 2012
  19. V. Vinothina, Dr. R. Sridaran, Dr. PadmavathiGanapathi," A Survey on Resource Allocation Strategies in Cloud Computing", (IJACSA) International Journal of Advanced Computer Science and Applications, Vol. 3, No. 6, 2012
Index Terms

Computer Science
Information Sciences

Keywords

Cloud Computing Energy consumption Bandwidth Consumption