• SHASHANK GIREPUNJE

Grid computation is new emerging area for researchers. The computing capabilities of grid system is comes from heterogeneous resources in order to support and manage complicated computing problems. Job scheduling in computing grid is a complex issue to be solved. Current scientific applications need huge computing power and storage space. However, to utilize computational grid efficiently, require an efficient job scheduling algorithm for proper management of resources in grids. In this paper, we propose a efficient Ant Colony Optimization (ACO) algorithm for job scheduling in the Grid environment. Using ant colony optimization with job selection approach, we can improve the efficiency of grid scheduling policy. In our approach, ant colony optimization and TLBO (teacher learning based optimization) is considered. The job selection is performed using TLBO method and the resource allocation is done through ant colony optimization.

"A novel ACO algorithm with job selection technique for job scheduling in Grid", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.62-66, June 2019, Available :http://www.jetir.org/papers/JETIR1907L63.pdf

"A novel ACO algorithm with job selection technique for job scheduling in Grid", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp62-66, June 2019, Available at : http://www.jetir.org/papers/JETIR1907L63.pdf