This paper addresses the problem of scheduling jobs in soft real-time systems, where the utility of completing each job decreases over time. We present a utility-based framework for making repeated scheduling decisions based on dynamically observed information about unscheduled jobs and system’s resources. This framework generalizes the standard scheduling problem to a resource-constrained envi...

This paper firstly summarizes and defines data grid models and the process of job scheduling, simultaneously analyzes the time and cost of job execution in the data grid. The job scheduling strategy influences the QoS of the data grid immediately and then proposes a design proposal of the job scheduling simulator of data grid based on a grid simulator named GridSim and introduces the architectu...

This paper presents an integrated approach for scheduling in distributed computing with strategies as sets of job supporting schedules generated by a critical works method. The strategies are implemented using a combination of job-flow and application-level techniques of scheduling within virtual organizations of Grid. Applications are regarded as compound jobs with a complex structure containi...

Gang scheduling has been widely used as a practical solution to the dynamic parallel job scheduling problem. Parallel threads of a single job are scheduled for simultaneous execution on a parallel computer even if the job does not fully utilize all available processors. Non allocated processors go idle for the duration of the time quantum assigned to the threads. In this paper we propose a clas...

Scheduling parallel jobs has been an active investigation area. The scheduler has to deal with heterogeneous workloads and try to obtain throughputs and response times such that ensures good performance. We propose a Dynamic Space-Sharing Scheduling technique, the Self Co-Scheduling, based on the combination of the best benefits from Static Space Sharing and Co-Scheduling. A job is allocated a ...

Grid computing plays the major role to solve very complex and computational problems in Scientific as well as in engineering fields where Resource management and Job scheduling plays crucial role. Most of the scheduling algorithms in Grid environment are based on FCFS with priority which is not suitable to give most optimal resource selection/job scheduling. We converted job scheduling problem ...

Scheduling for job shop is very important in both fields of production management and combinatorial op-timization. However, it is quite difficult to achieve an optimal solution to this problem with traditional opti-mization approaches owing to the high computational complexity. The combination of several optimization criteria induces additional complexity and new problems. In this paper, we pro...

Data Grid is a geographically distributed environment that deals with large-scale data-intensive problems. The main problems in data grid are job scheduling and data management. Generally, job scheduling in Grid has been studied from the perspective of computational Grid. In Data Grid, effective scheduling policy should consider both computational and data storage resources. In this paper a new...