Grid computing is a computation methodology using group of clusters connected over high-speed networks that involves coordinating and sharing computational power, data storage and network resources. Integrating a set of clusters of workstations into one large computing environment can improve the availability of computing power. The goal of scheduling is to achieve highest possible system throu...

A scheduling system is proposed and developed for a special type of flow shop. In this flow shop there is one machine at each stage. A job may require multiple operations at each stage. The first operation of a job on stage j cannot start until the last operation of the job on stage j-1 has finished. Preemption of the operations of a job is not allowed. The flow shop that we consider has anothe...

Two scheduling methods based on Extreme Value Theory (SEVAT) and Genetic Algorithms (GA) are developed. The SEVAT approach is a schedule building approach that creates a statistical profile of schedules through random sampling and predicts the potential' of a schedule alternative. The GA approach, on the other hand, is a schedule permutation approach, in which a population of schedules are init...

Correlations in traffic patterns are an important facet of the workloads faced by real systems, and one that has far-reaching consequences on the performance and optimization of the systems involved. However, all the existing analytical work on understanding the effect of correlations between successive service requirements (job sizes) is limited to First-Come-First-Served scheduling. This leav...

The execution of data intensive Grid applications raises several questions regarding job scheduling, data migration, and replication. This paper presents new scheduling algorithms using more sophisticated job behaviour descriptions that allow estimating job completion times more precisely thus improving scheduling decisions. Three approaches of providing input to the decision procedure are disc...

Problem statement: Meta-scheduling has become very important due to the increased number of submitted jobs for execution. Approach: We considered the job type in the scheduling decision that was not considered previously. Each job can be categorized into two types namely, dataintensive and computational-intensive in a specific ratio. Job ratio reflected the exact level of the job type in two sp...

Rapid development of the Internet of Things not only provides large amounts of data to the job-shop scheduling, but also proposes a great challenge for dynamic job shop scheduling. A dynamic job shop scheduling approach is proposed based on the data-driven genetic algorithm. Application examples suggest that this approach is correct, feasible and available. This approach can provide the technic...

One of the hot problems in grid computing is job scheduling. It is known that the job scheduling is NPcomplete, and thus the use of heuristics is the de facto approach to deal with this practice in its difficulty. The proposed is an imagination to fish swarm, job dispatcher and Visualization gridsim to execute some jobs. KEYWORD AFSA, Grid computing, scheduling, visualize, simulate, dispatcher,...

Processor allocation and job scheduling are two complementary techniques for improving the performance of parallel systems. This paper presents an effort in studying the issues of processor allocation and job scheduling on the emerging computing grid platform and developing an integrated approach to efficient workload management. The experimental results indicate that through careful design of ...