Abstract
Complexity of both data- intensive problems and computation-intensive problems has been increased in computational world. These problems require sophisticated mathematical & statistical techniques as well as knowledge creation and involve complex computations to be performed on huge amount of data. A number of large computational problems now work in terms of Petabytes of data rather than limited volume comprising of only Mbytes or Gbytes of data in olden days. In the present scenario, efficient utilization of system resources is necessary to solve large computational problems within desirable time constraint. In this paper, we present a dynamic load balancing algorithm for a cluster created by using heterogeneous commodity hardware. The algorithm uses system resources efficiently & effectively depending on the nature of the applications. Using this algorithm we observed an improvement in execution time of parallel applications if tasks are processed on favorable nodes instead of randomly assigned nodes.
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
Preview
Unable to display preview. Download preview PDF.
References
Li, X., Xiaodong, Z., Yanxia, Q.: Effective Load Sharing on Heterogeneous Networks of Workstations. In: 14th IEEE International Parallel & Distributed Processing Symposium, Mexico, pp. 431–438 (2000)
Xing, D., Xiaodong, Z.: Coordinating Parallel Processes on Networks of Workstation. J. Parallel and Distributed Computing 4(8), 125–135 (1997)
Huajie, Z.: On Load Balancing Model for Cluster Computers. International J. Computer Science and Network Security 8(10), 263–269 (2008)
Hong, J., et al.: Modeling Parallel Applications Performance on Heterogeneous Systems. In: 17th IEEE International Parallel & Distributed Processing Conference, France, pp. 201–205 (2003)
William, G., Ewing, L., Thakur, R.: Using MPI-2: Advanced Features of the Message-Passing Interface, http://www.mcs.anl.gov/research/projects/mpi
Sharma, R., Kanungo, P., Chandwani, M.: A Comparison of Computation Intensive and Data Intensive Problems on Heterogeneous Nodes in Network of Workstations. In: IEEE National Conference on Education & Research in Information Tecnology, Guna, pp. 291–298 (2010)
Xiaodong, Z., Yanxia, Q., Li, X.: Improving Distributed Workload Performance by Sharing Both CPU and Memory Resources. In: 20th International Conference on Distributed Computing Systems, Taiwan, pp. 233–241 (2000)
Maheshwari, P.: A Dynamic Load Balancing Algorithm for a Heterogeneous Computing Environment. In: 29th International Conference on System Sciences, Hawaii, pp. 338–346 (1996)
Post, E., Goosen, H.: Evaluating the Parallel Performance of a Heterogeneous System. In: 5th International Conference on High Performance Computing, Canberra, pp. 310–323 (2001)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Rajkumar, S., Priyesh, K., Manohar, C. (2011). A Destination Capability Aware Dynamic Load Balancing Algorithm for Heterogeneous Environment. In: Mantri, A., Nandi, S., Kumar, G., Kumar, S. (eds) High Performance Architecture and Grid Computing. HPAGC 2011. Communications in Computer and Information Science, vol 169. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22577-2_26
Download citation
DOI: https://doi.org/10.1007/978-3-642-22577-2_26
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-22576-5
Online ISBN: 978-3-642-22577-2
eBook Packages: Computer ScienceComputer Science (R0)