Grid computing utilizes the distributed heterogeneous resources in order to support complicated computing problems. Grid can be classified into two types: computing grid and data grid. Job scheduling in computing grid is a very important problem. To utilize grids efficiently, we need a good job scheduling algorithm to assign jobs to resources in grids. In the natural environment, the ants have ...

environment to solve larger scale computational applications. Grid computing contains resource management, job scheduling, security problems, information management and so on. Job scheduling is a fundamental and important issue in achieving high performance in grid computing systems. However, it is a big challenge to design an efficient scheduler and its implementation. In Grid Computing, there...

In this paper a new neuro-genetic architecture is presented that solves a profit oriented dynamic job shop problem. In the job shop order acceptance and scheduling problem new jobs arrive continuously and because of insufficient job shop capacity, a selection has to be made among the offered jobs. The goal is to find an order acceptance policy, which is supported by a scheduling policy, that ma...

The job shop scheduling problem (JSSP) has attracted much attention in the field of both information sciences and operations research. This paper considers the permutation Job shop scheduling problem with the objective of minimizing make span. Artificial Bee Colony algorithm (ABC) is one of the search heuristics used to solve global optimization problems in complex search spaces. It is observed...

This paper discusses two approaches to enhance multi-site scheduling for grid environments. First the potential improvements of multi-site scheduling by applying constraints for the job fragmentation are presented. Subsequently, an adaptive multi-site scheduling algorithm is pointed out and evaluated. The adaptive multi-site scheduling uses a simple decision rule whether to use or not to use mu...

The performance of job scheduling policies strongly depends on the properties of the incoming jobs. If the job characteristics often change, the scheduling policy should follow these changes. For this purpose the dynP job scheduler family has been developed. The idea is to dynamically switch the scheduling policy during runtime. In a basic version the policy switching is controlled by two param...

The Shortest Remaining Processing Time (SRPT) scheduling policy was proven, in the 1960s, to yield the smallest mean response time, and recently it was proven its performance gain over Processor Sharing (PS) usually does not come at the expense of large jobs. However, despite the many advantages of SRPT scheduling, it is not widely applied. One important reason for the sporadic application of S...

Data Grid is an infrastructure that controls huge amount of data files, and provides intensive computational resources across geographically distributed collaboration. The heterogeneity and geographic dispersion of grid resources and applications place some complex problems such as job scheduling. Most existing scheduling algorithms in Grids only focus on one kind of Grid jobs which can be data...

The performance of job scheduling algorithms in campus-wide PCcluster distributed computing environment may be influenced by several input variables (factors) such as sum of the job sizes of all the jobs in the workload, number of PCs in the cluster and even on the type of scheduling algorithm being used. Response surface methodology (RSM) based statistical regression techniques build empirical...