论文的主要研究成果包括：1设计了一种面向数据网格的分布式资源调度模型。
The contributions of the dissertation as follows: 1 a distributed resource scheduling model that adapt to the data grid.
在这种大规模的分布式环境中进行资源管理和应用调度是一项复杂的任务。
The management of resources and application scheduling in such a large-scale distributed environment is a complex task.
网格是一个分布式的异构资源环境，对作业提交和调度提出了更高的要求。
Grid is a distributed environment that integrates isomerous resources, so that it puts forword higher request for job submission and scheduling.
在分布式计算环境下，为了有效地利用计算资源、快速完成协同计算任务，提出了基于优先级的任务调度与负载均衡模型。
To utilize the computing resources effectively and accomplish the cooperative task rapidly in the distributed environment, the priorities based task scheduling and load balancing models are proposed.
目前研究的动态任务调度算法都基于集中式或部分分布式网格系统，系统中心节点(组)进行资源管理。
A dynamic scheduling algorithms studied in references are based on centralized grid system or part-distributed grid system, in which there are center node (s) to manage resources.
介绍了一种对CAN总线网络资源进行分布式调度的机制，满足分布式实时系统的实时性要求。
Introduced a mechanism to implement distributed scheduling for the CANBus resource in order to meet the requirement of a dynamic distributed real-time systems.
准确连续的资源监测与呈现是分布式计算性能调节与调度优化的关键。
Accurate, continuous resource monitoring and profiling are keys for enabling performance tuning and scheduling optimization.
准确连续的资源监测与呈现是分布式计算性能调节与调度优化的关键。
Accurate, continuous resource monitoring and profiling are keys for enabling performance tuning and scheduling optimization.
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