摘要
With Open Grid Service Architecture (OGSA) as system framework, and Globus Toolkit3.0 (GT3) as developing tools, Manufacturing Grid (MG) is proposed in this research to realize resource sharing and collaborative working among manufacturing resources, and task scheduling is one of the most critical components in this system. Nevertheless, the Globus Resource Allocation Manager (GRAM) does not provide scheduling system by default, and traditional performance-guided or economy-guided schedulers cannot satisfy our needs in MG. So, in this paper, a TQCS (Time, Quality, Cost, Service)-based scheduling approach is presented and the corresponding scheduler (Manufacturing Grid Task Scheduler, MGTS) is implemented with the functions of Global Process Planning (GPP) analyzing, resource discovery, resource selection, AHP (Analytic Hierarchy Process)-based resource mapping, and fault-tolerant handling. Furthermore, the application architecture is depicted at the end of the paper to illustrate the utilization of our scheduler.
With Open Grid Service Architecture (OGSA) as system framework, and Globus Toolkit3.0 (GT3) as developing tools, Manufacturing Grid (MG) is proposed in this research to realize resource sharing and collaborative working among manufacturing resources, and task scheduling is one of the most critical components in this system. Nevertheless, the Globus Resource Allocation Manager (GRAM) does not provide scheduling system by default, and traditional performance-guided or economy-guided schedulers cannot satisfy our needs in MG. So, in this paper, a TQCS (Time, Quality, Cost, Service)-based scheduling approach is presented and the corresponding scheduler (Manufacturing Grid Task Scheduler, MGTS) is implemented with the functions of Global Process Planning (GPP) analyzing, resource discovery, resource selection, AHP (Analytic Hierarchy Process)-based resource mapping, and fault-tolerant handling. Furthermore, the application architecture is depicted at the end of the paper to illustrate the utilization of our scheduler.
基金
This project is supported by Shanghai Science and Technology Committee (No. 025111055)
