In this paper, a genetic algorithm based approach for job scheduling in distributed system considering dynamic load balancing is discussed. The underlying distributed system has hierarchical structure and job scheduling is done in two levels: group level and node level. Scheduling in distributed system involves deciding not only when to execute a process, but also where to execute it. A proper ...

In the grid context, the scheduling can be grouped into two categories: offline scheduling and online scheduling. In the offline scheduling scenario, the sequence of jobs is known in advance, scheduling is based on information about all jobs in the sequence. While, in the online scheduling scenario a job is known only after all predecessors have been scheduled, and a job is scheduled only accor...

Cloud Computing is a revolutionary way of providing shared resources over the Internet. Through the use of low level virtualization software, the Cloud provides virtualized computing hardware infrastructure in a manner similar to the public utilities, thus it is also termed as Infrastructure-as-a-Service or Utility Computing. Job scheduling algorithms is one of the most challenging theoretical ...

Gang scheduling is a job scheduling policy for parallel computers that combines elements of space-sharing and time-sharing. In this paper, we analyze the performance of gang scheduling policies that allow the remapping of an executing job to a new set of processors. Most previously proposed gang-scheduling policies do not allow such job remapping under the assumption that it is prohibitively ex...

This paper is concerned with Batch Scheduling in job-shop like manufacturing systems. The Horizontal Scheduling approach is used, assuming that full scheduling of a simple or complex job, based on the job routing network of operations, from the first operation to the last, is performed before another job is considered for scheduling, having in consideration existing manufacturing processors and...

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 Flexible Job Shop Scheduling Problem (FJSP) is one of the most general and difficult of all traditional scheduling problems. The Flexible Job Shop Problem (FJSP) is an extension of the classical job shop scheduling problem which allows an operation to be processed by any machine from a given set. The problem is to assign each operation to a machine and to order the operations on the machine...

The Flexible Job Shop Scheduling Problem (FJSP) is one of the most general and difficult of all traditional scheduling problems. The Flexible Job Shop Problem (FJSP) is an extension of the classical job shop scheduling problem which allows an operation to be processed by any machine from a given set. The problem is to assign each operation to a machine and to order the operations on the machine...

Flexible job-shop scheduling problem derived from the job-shop scheduling problem, and is more realistic than the job-shop scheduling problem in the manufacturing enterprise. It should be utilized with high efficiency. But it is a multi-objective optimal problem. Three minimization objectives (Maximum completion time (makespan), Total workload of machines and Workload of the critical machine) a...