Comparative analysis of scheduling algorithms for grid computing

The grid computing offers powerful and dynamic framework, with the numerous resources, distributed CPU loads, along with the extent of idle memory continually altering. Efficient schedulers are required to schedule jobs in such dynamic environment. This paper presents comparative study of various well-known grid computing based scheduling techniques by taking into account the implementation environment as well as metrics used like soft computing, environment and metrics used with the aim to determine the effectiveness of each existing optimizing technique. This study has shown that the Ant colony optimization scheduling has quite significant results over the available techniques. However due to slowing growing rate it also become bottleneck of the optimistic scheduling. This paper ends up with the suitable future directions to enhance the existing scheduling techniques.