So for a university based cloud computing system to be economically viable, it requires a proper scheduling mechanism to monitor demand and allocate the system resources.
因此，大学内的云计算系统要想具有经济可行性，它需要一种适当的调度机制来监视需求并分配系统资源。
To learn more about scheduling, including those algorithms implemented in the Linux kernel, check out the scheduling (computing) page at Wikipedia.
要了解有关调度的更多信息，包括那些在Linux内核中实现的算法，请在Wikipedia中查看调度(计算)页面。
Scheduling of heterogeneous system takes aim at balancing computing load and getting minimal parallel execute time.
异构系统上调度的目标是平衡计算负载，以获得最短的并行计算时间。
According to critical path method and serial scheduling, a schema was discussed for computing time parameters of transitive predecessors and transitive successors.
根据关键路径法和串行调度原理，论述了先序活动和后序活动时间参数计算的方法，并以实例阐述了计算原理。
Data broadcast scheduling is one of hot area of data management technology in mobile computing environments.
数据广播调度是移动计算环境中数据管理技术的研究热点之一。
Different resource scheduling algorisms are designed for different computing expectation in order to achieve flexible and efficiency grid resource schedule.
针对不同的“计算期望”，设计了不同的资源调度算法，以实现高效，灵活的网格资源调度。
Task scheduling is an important component of grid computing system.
任务调度是网格计算系统的一个重要组成部分。
If the grid system itself or the administrator wants to schedule and optimize the grid computing in a scientific way, there need some good scheduling and optimizing schemas.
网格系统自身或管理者要想根据网络连接状况科学地调度、优化计算过程，这需要一定的调度、优化方案。
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.
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 deal with the load balancing and fault tolerance in grid computing environment, a distributed scheduling model oriented to tradition and grid service execution mechanisms was proposed.
为有效解决网格计算环境中的负载平衡和容错问题，提出了面向传统和服务执行方式的分布式调度模型。
This paper describes how to carry out task mapping and scheduling in heterogeneous computing system (HCS) using list scheduling algorithms.
研究了在异构计算系统(HCS)中利用表调度式算法进行任务映射与调度。
Task scheduling is an important part in Grid computing. As it has been proven to be NP-complete, it is adaptive to be solved by heuristics.
在网格计算中，任务调度是一个重要的组成部分，并被证明为NP完全问题，以启发式方法求解较为适合。
Good performance is achieved by using AGA in the scheduling of tasks in the grid computing pool.
将该算法应用于计算池的任务调度取得了较好的效果。
This paper established a model on the flexibility of short-term scheduling for multipurpose batch process, and developed an applicable computing program to solve the MINLP model.
本文建立了一个多目的间歇过程短期排程柔性的模型，并开发了一个实用的计算程序求解此MINLP模型。
Since the resource has the characteristics of dynamics and heterogeneous, task scheduling becomes a very complex and challenging problem in the grid computing.
由于资源具有异构、动态等特性，计算网格环境下的调度就成了一个非常复杂且具有挑战性的问题。
Job scheduling is a key part in the computing grid system, a good scheduling method could enhance the performance of entire system.
任务调度是计算网格系统中极其关键的一部分，一种好的调度方法可以极大地提高整个系统的性能。
A good strategy of grid scheduling is needed to allocate resources effectively in order to get the better performance and reduce total execution time and cost in grid computing.
为了使网格达到最大的性能，有效降低网格计算的执行时间和耗费，需要一个良好的资源调度策略来有效的分配网格资源。
Considering the complexity and essentiality of the task scheduling, it becomes an important issue in the study field of the grid computing.
由于其复杂性及重要性，任务调度成为了网格计算研究领域的一个焦点。
Resources scheduling is one of core technologies of grid computing.
资源调度技术是网格核心服务之一。
The main goal of grid task scheduling is to maximum its system throughput and to match the application's needs with the available computing resources.
网格调度追求的目标是在把可用资源调度给需要的应用任务的同时，使系统获得最高的吞吐率。
To improve the system performance and execute the applications that users submit, the optical network based distributed computing system needs an efficient task scheduling algorithm.
为了能够提高系统效率，尽快的执行用户提交的应用，基于光网络的分布式计算系统需要一个有效的调度算法。
The complex resources and tasks in Grid computing environment make it very difficult to validate the methods of resource management and task scheduling.
网格环境中的资源情况和任务情况异常复杂，难以用实验测试各种资源管理和任务调度方法的有效性。
Trust is an important factor for scheduling in grid environments. It is also a pivotal technology for the efficiency and performance of grid computing.
信任是网格资源调度中一个很重要的因素，也是影响网格计算有效性和性能的关键技术之一。
In grid computing, relative performance of two scheduling algorithms on sharing resources and exclusive resources may be different.
在网格中，两种算法在资源共享时和资源独占时的性能优劣对比可能不同。
In grid computing, relative performance of two scheduling algorithms on sharing resources and exclusive resources may be different.
在网格中，两种算法在资源共享时和资源独占时的性能优劣对比可能不同。
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