Cloud Computing is an emerging area in the field of information technology (IT). Load balancing is one of the main challenges in cloud computing. It is a technique which is required to distribute the dynamic workload across multiple nodes to ensure that no single node is overloaded. Load balancing techniques help in optimal utilization of resources and hence in enhancing the performance of the system. The goal of load balancing is to minimize the resource consumption which will further reduce energy consumption and carbon emission rate that is the dire need of cloud computing. This determines the need of new metrics, energy consumption and carbon emission for energy-efficient load balancing in cloud computing. This paper mainly focused on the concept of load balancing technique in cloud computing, the existing load balancing techniques and also discusses the different qualitative metrics or parameters like performance, scalability, associated overhead etc.

 

Published In : IJCSN Journal Volume 3, Issue 1

Date of Publication : 01 February 2014

Pages : 01 - 08

Figures : 01

Tables : --

Publication Link : IJCSN-2014/3-1/Load-Balancing-Techniques-Major-Challenges-in-Cloud-Computing-A-Systematic-Review

 

 

 

Jasobanta Laha : Computer Science., Biju Patnaik University of Technology (BPUT) Rourkela, Odisha, 769001, India

Rabinarayan Satpathy : Computer Science., Biju Patnaik University of Technology (BPUT) Rourkela, Odisha, 769001, India

Kaustuva Dev : Computer Science., Biju Patnaik University of Technology (BPUT) Rourkela, Odisha, 769001, India

 

 

 

 

 

 

 

Load Balancing

Green Computing

Carbon Emission

Dynamic Load Balancing

Workload and Client aware policy (WCAP)

ACCLB

CARTON

VectorDot.

Load balancing is one of the major challenges in cloud computing. It is a mechanism which distributes the dynamic local workload evenly across all the nodes in the whole cloud. This will avoid the situation where some nodes are heavily loaded while others are idle or doing little work. It helps to achieve a high user satisfaction and resource utilization ratio. Hence, this will improve the overall performance and resource utility of the system. It also ensures that every computing resource is distributed efficiently and fairly. With proper load balancing, resource consumption can be kept to a minimum which will further reduce energy consumption and carbon emission rate which is a dire need of cloud computing. Existing load balancing techniques that have been discussed mainly focus on reducing associated overhead, service response time and improving performance etc. but none of the techniques has considered the energy consumption and carbon emission factors. But still there are many existing issues like Load Balancing, Virtual Machine Migration, Server Consolidation, Energy Management, etc. which have not been fully addressed. Central to these issues is the issue of load balancing, that is required to distribute the excess dynamic local workload evenly to all the nodes in the whole Cloud to achieve a high user satisfaction and resource utilization ratio.

 

 

 

 

 

 

 

 

 

[1] B. P. Rima, E. Choi, and I. Lumb, “A Taxonomy and Survey of Cloud Computing Systems”, Proceedings of 5th IEEE International Joint Conference on INC, IMS and IDC, Seoul, Korea, August 2009, pages 44-51.

[2] A. M. Alakeel, “A Guide to dynamic Load balancing in Distributed Computer Systems”, International Journal of Computer Science and Network Security (IJCSNS), Vol. 10, No. 6, June 2010, pages 153-160.

[3] B. P. Rimal, E. Choi, and I. Lumb, “A Taxonomy, Survey, and Issues of Cloud Computing Ecosystems, Cloud Computing: Principles, Systems and Applications”, Computer Communications and Networks, Chapter 2 , pages 21-46, DOI 10.1007/978-1-84996-241-42, Springer – V erlagLondonLimited, 2010.

[4] R. Mata-Toledo, and P. Gupta, “Green data center: how green can we perform”, Journal of Technology Research, Academic and Business Research Institute, Vol. 2, No. 1, May 2010, pages 1-8.

[5] S. Kabiraj, V. Topka, and R. C. Walke, “Going Green: A Holistic Approach to Transform Business”, International Journal of Managing Information Technology (IJMIT), Vol. 2, No. 3, August 2010, pages 22-31.

[6] J. Baliga, R. W. A. Ayre, K. Hinton, and R. S. Tucker, “Green Cloud Computing: Balancing Energy in Processing, Storage, and Transport”, Proceedings of the IEEE, Vol. 99, No. 1, January 2011, pages 149-167.

[7] Sandeep Sharma, Sarabjeet Singh, Meenaksshi Sharma, “Performance Analysis of Load Balancing Algorithms”, World Academy of Science, Engineering and Technology, 2008.

[8] Hisao Kameda, EL-Zoghdy Said Fathyy and Inhwan Ryuz Jie Lix, “A Performance Comparison of Dynamic vs Static Load Balancing Policies in a Mainframe, Personal Computer Network Model”, Proceedings Of The 39th IEEE Conference on Decision & Control, 2000.

[9] Ali M Alakeel, “A Guide To Dynamic Load Balancing In Distributed Computer Systems”, International Journal of Computer Science and Network Security, Vol. 10 No. 6, June 2010.

[10] Z. Zhang, and X. Zhang, “A Load Balancing Mechanism Based on Ant Colony and Complex Network Theory in Open Cloud Computing Federation”, Proceedings of 2nd International Conference on Industrial Mechatronics and Automation ICIMA), Wuhan, China, May 2010, pages 240- 243.

[11] Nidhi Jain Kansal, Inderveer Chana, “Cloud Load Balancing Techniques: A Step Towards Green Computing”, IJCSI, Vol. 9, Issue 1, January 2012.

[12] R. X. T. and X. F. Z.. A Load Balancing Strategy Based on the Combination of Static and Dynamic, in Database Technology and Applications (DBTA), 2010 2nd International Workshop (2010), pp. 1-4.

[13] H. Mehta, P. Kanungo, and M. Chandwani, “Decentralized content aware load balancing algorithm for distributed computing environments”, Proceedings of the International Conference Workshop on Emerging Trends in Technology (ICWET), February 2011, pages 370-375.

[14] A. M. Nakai, E. Madeira, and L. E. Buzato, “Load Balancing for Internet Distributed Services Using Limited Redirection Rates”, 5th IEEE Latin-American Symposium on Dependable Computing (LADC), 2011, pages 156-165.

[15] Y. Lua, Q. Xiea, G. Kliotb, A. Gellerb, J. R. Larusb, and A. Greenber, “Join-Idle-Queue: A novel load balancing algorithm for dynamically scalable web services”, An international Journal on Performance evaluation, In Press, Accepted Manuscript, Available online 3 August 2011.

[16] Xi. Liu, Lei. Pan, Chong-Jun. Wang, and Jun-Yuan. Xie, “A Lock-Free Solution for Load Balancing in Multi-Core Environment”, 3rd IEEE International Workshop on Intelligent Systems and Applications (ISA), 2011, pages 1-4.

[17] J. Hu, J. Gu, G. Sun, and T. Zhao, “A Scheduling Strategy on Load Balancing of Virtual Machine Resources in Cloud Computing Environment”, Third International Symposium on Parallel Architectures, Algorithms and Programming (PAAP), 2010, pages 89-96.

[18] A. Bhadani, and S. Chaudhary, “Performance evaluation of web servers using central load balancing policy over virtual machines on cloud”, Proceedings of the Third Annual ACM Bangalore Conference (COMPUTE), January 2010.

[19] H. Liu, S. Liu, X. Meng, C. Yang, and Y. Zhang, “LBVS: A Load Balancing Strategy for Virtual Storage”, International Conference on Service Sciences (ICSS), IEEE, 2010, pages 257-262.

[20] Y. Fang, F. Wang, and J. Ge, “A Task Scheduling Algorithm Based on Load Balancing in Cloud Computing”, Web Information Systems and Mining, Lecture Notes in Computer Science, Vol. 6318, 2010, pages 271-277.

[21] YashpalsinhJadeja, KiritModi, 2012 "Cloud Computing- Concepts, Architecture and Challenges"International Conference on Computing, Electronics and Electrical Technologies, IEEE, pp: 4/12.

[22] M. Randles, D. Lamb, and A. Taleb-Bendiab, “A Comparative Study into Distributed Load Balancing Algorithms for Cloud Computing”, Proceedings of 24th IEEE International Conference on Advanced Information Networking and Applications Workshops, Perth, Australia, April 2010, pages 551-556.

[23] http://www.loadbalancing.org/

[24] Z. Zhang, and X. Zhang, “A Load Balancing Mechanism Based on Ant Colony and Complex Network Theory in Open Cloud Computing Federation”, Proceedings of 2nd International Conference on Industrial Mechatronics and Automation (ICIMA), Wuhan, China, May 2010, pages 240- 243.

[25] S. Wang, K. Yan, W. Liao, and S. Wang, “Towards a Load Balancing in a Three-level Cloud Computing Network”, Proceedings of the 3rd IEEE International Conference on Computer Science and Information Technology (ICCSIT), Chengdu, China, September 2010, pages 108-113.

[26] V. Nae, R. Prodan, and T. Fahringer, “Cost-Efficient Hosting and Load Balancing of Massively Multiplayer Online Games”, Proceedings of the 11th IEEE/ACM International Conference on Grid Computing (Grid), IEEE Computer Society, October 2010, pages 9-17.

[27] R. Stanojevic, and R. Shorten, “Load balancing vs. distributed rate limiting: a unifying framework for cloud control”, Proceedings of IEEE ICC, Dresden, Germany, August 2009, pages 1-6.

[28] Y. Zhao, and W. Huang, “Adaptive Distributed Load Balancing Algorithm based on Live Migration of Virtual Machines in Cloud”, Proceedings of 5th IEEE International Joint Conference on INC, IMS and IDC, Seoul, Republic of Korea, August 2009, pages 170-175.

[29] A. Singh, M. Korupolu, and D. Mohapatra, “Server-storage virtualization: integration and load balancing in data centers”, Proceedings of the ACM/IEEE conference on Supercomputing (SC), November 2008.

[30] A Book by O’ Reilly on “Cloud Security And Privacy”.

[31] Sri Varsha Gorge, Virajith Jalaparti and Harini Vaidhyanathan “Multi-Tier Distributed Load Balancing” CS598RHC Literature Survey.

[32] A. Khiyaita, M. Zbakh, H. El Bakkali and Dafir El Kettani, “Load Balancing Cloud Computing: State of Art” , 9778-1- 4673-1053-6/12/$31.00, 2012 IEEE.