Grid computing is a growing technology, which have hundreds or thousands of computational nodes to execute large applications. The main issues consider in grid computing is Load balancing, Fault tolerant and Fault recovery. In order to utilize the resource efficiently and to satisfy all the requirements of the user, there is need for effective scheduling algorithm. Scheduler schedule job to available resources in the sites and result submit to user. Otherwise if any faults detects by fault detector, In the event of failures, how to execute the job from the processor failure. Since grid is more difficult, complex to implement and manage, so there could be the differences in their performance under diverse experimental conditions. We should modify the algorithm. To achieve high throughput and proper resource utilization we purpose Min-Max fair scheduling algorithm for load balancing. This paper focus on how to increase performance of Grid Environment. The proposed system builds on using Grid Simulation Toolkit (Gridsim).

Load Balancing, Grid Computing, Fault Tolerant & Fault Recovery, Min-Max Fair Scheduling algorithm

Nikolaos D, Doulamis, Anastsios D. Doulamis, Emmanouel A. Varvarigos and Theodora A. Varvarigou, ”Fair scheduling algorithm in grids”, IEEE transactions on parallel and distributed systems, Vol. 18, No.11, November 2007, pp. 1630-1648.
[2] Buyya, R., Abramson, J., and Giddy, j/ Nimrod/G: architecture for a resource management and scheduling system in a global computational Grid. 4th IEEE conf. on High-performance computing, 2000.
[3] Kai lu and Albert Y.Zomaya “A Hybrid policy for Job Scheduling and Load Balancing in Heterogeneous Computational Grids” 6th International Symposium on parallel and Distributed Computing, IEEE, 2007.
[4] Manish Arora, Sajal K. Das and Rupak Biswas “A De-centralized Scheduling and Load Balancing Algorithm for Heterogeneous Grid Environments”, Proceeding of the International Conference on Parallel Processing Workshops, IEEE, 2002, pp. 1-7.
[5] Yajun Li, Yuhang Yang and Rongbo Zhu “A Hybrid Load balancing Strategy of Sequential Tasks for Computational Grids”, International Conference on Networking and Digital Society, IEEE, 2009, pp. 112-117.
[6] S.K. Karthik Kumar, M. Udhaya Preethi and P. Chitra “Fair Scheduling Approach for Load Balancing and Fault Tolerant in grid environment”, IEEE International Conference on Emerging Trends in Computing, Communication and Nanotechnology, 2013. pp. 446-451.
[7] Jing Wei-peng, liu Ya-qiu and Wu Qu “Fault-tolerant task scheduling in Multiprocessor systems based on Primary-Backup Scheme”, IEEE, 2010, pp. 670-675.
[8] Jasma balasangameshwara, Nedunchezhian Raju “A Hybrid policy for fault tolerant load balancing in grid computing environment”, Journal of network and Computer Applications, Vol. 35, Issue 1, January 2012.
[9] Hwang s, Kesselman C,”A flexible framework for fault tolerance in the grid”, Journal of grid computing, 2003.
[10] N. Budhiraja et al., S. Mulender “The primary Backup Approach”, Distributed systems, pp.169-197, 1993.
[11] Li K, “Optimal load distribution in non dedicated heterogeneous cluster and grid computing environment”, Journal of Systems Architecture: The EUROMICRO Journal 2008.
[12] Nandagopal Malarvizhi, Rhymend Uthariaraj V, “Decentralized dynamic load balancing for multi cluster grid environment” Future Generation Computer Systems 2009.
[13] L. Anand, D. Dhose, V. Mani, “ELISA: An estimated load information scheduling algorithm for distributed computing systems”, Computers & Mathematics with applications, Vol. 37, Issue 8, April 1999.