A Comparative Study of Load Balancing Algorithms in Cloud Computing Environment

Cloud Computing is a new trend emerging in IT environment with huge requirements of infrastructure and resources. Load Balancing is an important aspect of cloud computing environment. Efficient load balancing scheme ensures efficient resource utilization by provisioning of resources to cloud users on demand basis in pay as you say manner. Load Balancing may even support prioritizing users by applying appropriate scheduling criteria. This paper presents various load balancing schemes in different cloud environment based on requirements specified in Service Level Agreement (SLA).

[1]  Rajkumar Buyya,et al.  CloudSim: a toolkit for modeling and simulation of cloud computing environments and evaluation of resource provisioning algorithms , 2011, Softw. Pract. Exp..

[2]  Raouf Boutaba,et al.  Cloud computing: state-of-the-art and research challenges , 2010, Journal of Internet Services and Applications.

[3]  Dan Wang,et al.  Cloud Task Scheduling Based on Load Balancing Ant Colony Optimization , 2011, 2011 Sixth Annual Chinagrid Conference.

[4]  Mario Zagar,et al.  Analysis of issues with load balancing algorithms in hosted (cloud) environments , 2011, 2011 Proceedings of the 34th International Convention MIPRO.

[5]  Rajkumar Buyya,et al.  Modeling and simulation of scalable Cloud computing environments and the CloudSim toolkit: Challenges and opportunities , 2009, 2009 International Conference on High Performance Computing & Simulation.

[6]  A. Taleb-Bendiab,et al.  A Comparative Study into Distributed Load Balancing Algorithms for Cloud Computing , 2010, 2010 IEEE 24th International Conference on Advanced Information Networking and Applications Workshops.

[7]  Li-zhen Cui,et al.  A Multiple QoS Constrained Scheduling Strategy of Multiple Workflows for Cloud Computing , 2009, 2009 IEEE International Symposium on Parallel and Distributed Processing with Applications.

[8]  Jian Xie,et al.  Independent Tasks Scheduling Based on Genetic Algorithm in Cloud Computing , 2009, 2009 5th International Conference on Wireless Communications, Networking and Mobile Computing.

[9]  Nader Mohamed,et al.  A Survey of Load Balancing in Cloud Computing: Challenges and Algorithms , 2012, 2012 Second Symposium on Network Cloud Computing and Applications.

[10]  L. Youseff,et al.  Toward a Unified Ontology of Cloud Computing , 2008, 2008 Grid Computing Environments Workshop.

[11]  Bingchiang Jeng,et al.  Load-Balancing Tactics in Cloud , 2011, 2011 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery.

[12]  Martin Randles,et al.  Cross Layer Dynamics in Self-Organising Service Oriented Architectures , 2008, IWSOS.

[13]  Kobra Etminani,et al.  A Min-Min Max-Min Selective Algorithm for Grid Task Scheduling , 2007, 2007 3rd IEEE/IFIP International Conference in Central Asia on Internet.

[14]  eva Kühn,et al.  Applying Swarm Intelligence Algorithms for Dynamic Load Balancing to a Cloud Based Call Center , 2010, 2010 Fourth IEEE International Conference on Self-Adaptive and Self-Organizing Systems.

[15]  Zhuolin Yang,et al.  Virtualization security for cloud computing service , 2011, 2011 International Conference on Cloud and Service Computing.

[16]  Kuo-Qin Yan,et al.  Towards a Load Balancing in a three-level cloud computing network , 2010, 2010 3rd International Conference on Computer Science and Information Technology.

[17]  Xiao Liu,et al.  A market-oriented hierarchical scheduling strategy in cloud workflow systems , 2011, The Journal of Supercomputing.

[18]  Yong Zhao,et al.  Cloud Computing and Grid Computing 360-Degree Compared , 2008, GCE 2008.

[19]  Shu-Chin Wang,et al.  A Three-Phases Scheduling in a Hierarchical Cloud Computing Network , 2011, 2011 Third International Conference on Communications and Mobile Computing.

[20]  Borja Sotomayor,et al.  Virtual Infrastructure Management in Private and Hybrid Clouds , 2009, IEEE Internet Computing.