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A METHOD AND SYSTEM FOR JOB SCHEDULING IN DISTRIBUTED DATA PROCESSING SYSTEM WITH IDENTIFICATION OF OPTIMAL NETWORK TOPOLOGY

机译:识别最优网络拓扑的分布式数据处理系统中的作业调度方法和系统

摘要

The method of the present invention provides an automatic and optimised selection of the network topology for distributing scheduling of jobs on the computers of the modified network topology. The automatic and optimised selection of the network topology starts from the current topology and a desired number of additional connections. In this way the method of the present invention provides a higher convergence speed for the modified consensus algorithm in comparison e.g. to a simple ring network. The method exploits the so called small-world networks. Small-world networks are more robust to perturbations than other network architectures. The preferred embodiment provides a workload scheduling system which is highly scalable to accommodate increasing workloads within a heterogeneous distributed computing environment. A modified average consensus algorithm is used to distribute network traffic and jobs amongst a plurality of computers.
机译:本发明的方法提供了网络拓扑的自动和优化选择,用于在修改后的网络拓扑的计算机上分配作业的调度。网络拓扑的自动和优化选择从当前拓扑和所需数量的附加连接开始。以这种方式,本发明的方法与例如图1相比,为修改后的共识算法提供了更高的收敛速度。到简单的环形网络。该方法利用了所谓的小世界网络。小世界网络比其他网络体系结构对干扰的鲁棒性更高。优选实施例提供了一种工作负载调度系统,该系统具有高度可扩展性,以适应异构分布式计算环境中不断增加的工作负载。修改后的平均共识算法用于在多个计算机之间分配网络流量和作业。

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