Abstract
Load balancing is the process of distributing tasks among different nodes in a network. The nodes may be either on different machines or nodes (virtual machines) on the same machine. Based on the availability of the nodes, processes from fully loaded node can be migrated from one node to another having less load known as process migration. Process migration can also be done in the virtualization environment by using a hypervisor called Xen hypervisor. This hypervisor safely multiplexes the hardware resources of the physical machine leading the resource allocation in the Virtual Machine (VM) to improve the utilization and performance. To optimize the task of balancing load among nodes, Genetic algorithm (GA) may be used for selecting the destination. GA is a search algorithm, based on natural genetics and principle of evolution and is been widely used in optimization with binary and continuous variables. With the adaptive crossover operation of GA and the searching heuristic and fitness function, lots of possible solutions are searched and the best one is selected as the destination for migration. GA is been proved to be effective in discovering the global optimum even in a very complex searching space.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Zarrabi, A.: Generic process migration algorithm. Int. J. Distrib. Parallel Syst. (IJDPS) 3(5), September (2012)
Li,, Z., Dong, Y.-M., Huang, C.-Y.: A study of link load balancing based on improved genetic algorithm, 6th International Symposium on Computational Intelligence and Design (2013)
A survey of parallel genetic algorithms by Erick Cantú-Paz, Department of Computer Science and Illinois Genetic Algorithms Laboratory, University of Illinois, Urbana-Champaign
Thibault, S., Deegan, T.: Improving performance by embedding hpc applications in lightweight xen domains. In: 2nd International Workshop on Virtualization Technology in Distributed Computing (VTDC), IEEE (2006)
Ning, G., Sun, Y.: Research and implementation of resource management system based on xen virtual machine. In: International Conference on Computer Science and Network Technology (2011)
Youseff, L., Wolski, R., Gorda, B., Krintz, C.: Evaluating the performance impact of Xen on MPI and process execution for HPC systems. 2nd International Workshop on Virtualization Technology in Distributed Computing (VTDC), IEEE (2006)
Xen Hypervisor Deployment, Management, and Cloud Computing Tools, Todd Deshane and Patrick F. Wilbur Clarkson University
Liu, F., Zhou, W., Zhou, M.: A Xen-based data sharing & access controlling method. 3rd International Symposium on Intelligent Information Technology Application (2009)
Ranjitha, K., Sandhya, S., Cauvery, N.K.: A survey on: pre-emptive migration of a video process using genetic algorithm on virtual machine. Int. J. Eng. Comput. Sci. ISSN:2319-7242 3(5), pp. 5897-5900 may (2014)
Mergen, M.F., Uhlig, V., Krieger, O., Xenidis, J.: Virtualization for High-Performance Computing, IBM T. J. Watson Research Center, Yorktown Heights
Milojicic, D.S., Douglis, F., Paindaveine, Y., Wheeler, R., Zhou, S.: Process Migration, HP Labs, AT&T Labs–Research, TOG Research Institute, EMC, University of Toronto and Platform Computing, August 10 (1999)
Sandhya, S., Cauvery, N.K.: An improved and optimized approach for pre-emptive migration of video process, 978-1-4799-6629-5/14/$31.00 IEEE (2014)
Mcheick, H., Mohammed, Z.R., Lakiss, A.: Evaluation of load balance algorithms. 9th International Conference on Software Engineering Research, Management and Applications (2011)
Sandhya S., Cauvery, N.K.: Dynamic load balancing for video processing system in cloud I.K. Sethi (ed.), Computational Vision and Robotics, Advances in Intelligent Systems and Computing 332, DOI 10.1007/978-81-322-2196-8_22, Springer India 2015
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer India
About this paper
Cite this paper
Sandhya, S., Usha, N., Cauvery, N.K. (2016). Load Based Migration Based on Virtualization Using Genetic Algorithm. In: Shetty, N., Prasad, N., Nalini, N. (eds) Emerging Research in Computing, Information, Communication and Applications. Springer, New Delhi. https://doi.org/10.1007/978-81-322-2553-9_29
Download citation
DOI: https://doi.org/10.1007/978-81-322-2553-9_29
Published:
Publisher Name: Springer, New Delhi
Print ISBN: 978-81-322-2552-2
Online ISBN: 978-81-322-2553-9
eBook Packages: EngineeringEngineering (R0)