TY - JFULL AU - T. Vigneswari and M. A. Maluk Mohamed PY - 2014/12/ TI - Optimal Grid Scheduling Using Improved Artificial Bee Colony Algorithm T2 - International Journal of Computer and Information Engineering SP - 2069 EP - 2078 VL - 8 SN - 1307-6892 UR - https://publications.waset.org/pdf/10000486 PU - World Academy of Science, Engineering and Technology NX - Open Science Index 95, 2014 N2 - Job Scheduling plays an important role for efficient utilization of grid resources available across different domains and geographical zones. Scheduling of jobs is challenging and NPcomplete. Evolutionary / Swarm Intelligence algorithms have been extensively used to address the NP problem in grid scheduling. Artificial Bee Colony (ABC) has been proposed for optimization problems based on foraging behaviour of bees. This work proposes a modified ABC algorithm, Cluster Heterogeneous Earliest First Min- Min Artificial Bee Colony (CHMM-ABC), to optimally schedule jobs for the available resources. The proposed model utilizes a novel Heterogeneous Earliest Finish Time (HEFT) Heuristic Algorithm along with Min-Min algorithm to identify the initial food source. Simulation results show the performance improvement of the proposed algorithm over other swarm intelligence techniques. ER -