Design of G-CODE algorithms and components

G-CODE算法和组件的设计

• 批准号: 238997-2006
• 负责人: Aggarwal, AkshaiKumar
• 金额: $ 0.84万
• 依托单位: University of Windsor
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2006
• 资助国家: 加拿大
• 起止时间: 2006-01-01 至 2007-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=337843
• 关键词: Design; CODE; algorithms; components

The research aims at developing algorithms and protocols required for an optimized network- aware scheduler for the Grid Computing Development Environment (G-CODE) system. The scheduler may use sender-side algorithm and historical experience to estimate bandwidth. It would use heuristic techniques like genetic algorithm to obtain a near-optimal schedule in near-real time. In early nineties, the traffic models using self-similar processes and long range dependencies were used. However the studies conducted in 2000 have shown that traffic follows Poisson distribution. We, therefore, propose to investigate a self-induced sender-side algorithm based on Poisson distribution. The Meta scheduler is to permit advance reservations and work-flow based task scheduling. We propose to investigate the use of genetic algorithm up to the lowest level, where its use may depend upon the depth of parallelism of the application. If the resources are represented by a dynamic graph, if each node is represented by a tuple and if applications are represented by graphs with dual weights, optimization process will match the requirements of the processes of an application with the compute-powers of  the heterogeneous nodes, after considering the  communication delays, latencies, prior reservations and the trust that the client is able to build. NOVELTIES OF THE WORK: There is no reported scheduler with sender-end bandwidth algorithm and with the ability to handle workflow type of jobs, prior reservations or communication delays. The scheduler algorithms become too slow, when even a thousand processes are required to be mapped. None of them tries to continuously evaluate trust factor at every level. Moreover our research is trying to develop algorithms and protocols, which are in alignment with the moving target of open Grid Computing standards. EXPECTED SIGNIFICANCE: The new approaches mentioned here are worth exploring if we are to progress towards the vision of a global grid, with unlimited number of ubiquitous devices connected to it.

该研究旨在为网格计算开发环境(G-CODE)系统开发优化的网络感知调度器所需的算法和协议。调度器可以使用发送端算法和历史经验来估计带宽。它将使用遗传算法等启发式技术来近乎实时地获得接近最优的调度。在90年代初，使用了使用自相似过程和长范围相关性的流量模型。然而，2000年进行的研究表明，交通流量服从泊松分布。因此，我们建议研究一种基于泊松分布的自诱导发送方算法。元调度器允许提前预订和基于工作流的任务调度。我们建议调查遗传算法的使用直到最低水平，其中它的使用可能取决于应用程序的并行性的深度。如果资源由动态图表示，如果每个节点由元组表示，如果应用程序由具有双权重的图表示，则优化过程将在考虑了较低的通信延迟、延迟、事先预留和客户端能够建立的信任后，将应用程序的进程要求与所有异类节点的计算能力相匹配。工作的新颖性：没有报道具有发送端带宽算法的调度器，并且能够处理工作流类型的作业、预先预订或通信延迟。即使需要映射一千个进程，调度器算法也会变得太慢。他们中没有一个人试图在每个层面上持续评估信任因素。此外，我们的研究还在努力开发符合开放网格计算标准的移动目标的算法和协议。预期意义：如果我们要朝着全球电网的愿景前进，并将无限数量的无处不在的设备连接到它，这里提到的新方法是值得探索的。