SCORE: A Scalable Architecture for Implementing Resource Management Algorithms in High Speed Networks

SCORE：用于在高速网络中实施资源管理算法的可扩展架构

• 批准号: 9814929
• 负责人: Hui Zhang
• 金额: $ 48.56万
• 依托单位: Carnegie-Mellon University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 1999
• 资助国家: 美国
• 起止时间: 1999-09-15 至 2003-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9814929&HistoricalAwards=false
• 关键词: SCORE; Scalable; Architecture; Implementing; Resource

The ability to support per-flow management -- that is, to maintain state, manage buffers, perform packet classification and/or scheduling on a per flow basis -- provides a powerful tool to address many of the challenging resource management problems in today's Internet, such as congestion control andend-to-end quality of service. However, given that the number of flows in a backbone routers can be on the order of hundred of thousands, the complexity incurred by per-flow management mechanisms may prevent them from being effectively implemented and widely deployed.To address these problems, the principal investigator (PI) proposes an architecture, called Scalable Core (SCORE for short) in which the network is partitioned in continuous regions, called islands. Within each island the PI distinguishes between edge and core nodes. While the edge nodes perform per flow management, the core nodes do not. Since edge nodes manage fewer flows and at the limit an edge node can be a host, this architecture is highly scalable. The main goal is then to use the SCORE architecture to approximate a reference island in which all nodes perform per flow management. In this way it is possible to provideefficient support for a wide variety of resource management policies.To approximate the reference network the PI introduces two schemes. In the first scheme, each ingress node labels every packet as it enters the network with the state of the flow (e.g., rate) to which it belongs. Further, each core node processes the packet based on its label and the node state (e.g., utilization). In the second scheme, the states of all nodes on the flow's path are aggregated and sent to the edge nodes. Based on this information and the flow state, the edge routers decide how to process an incoming packet (e.g., forward or drop it).The PI plans to develop an integrated set of algorithms within the SCORE framework to support congestion control for best-effort service, end-to-end QoS guarantee, and differential services. He will conduct the study via a combination of analysis, simulation, and implementation. In addition, he plans to conduct scaled experiments over the CAIRN high speed testbed network and work with industrial partners (Cisco, Ascend, 3Com, Intel, MCI) to speed-up the transition of the developed technologies to the industry. The results of this work are expected to have significant impacts on the design of resource management algorithms for the Internet.

支持每流管理的能力——即维护状态、管理缓冲区、在每流的基础上执行数据包分类和/或调度——提供了一个强大的工具来解决当今互联网中许多具有挑战性的资源管理问题，例如拥塞控制和端到端服务质量。然而，考虑到骨干路由器中的流数量可能达到数十万量级，每流管理机制所带来的复杂性可能会阻碍其有效实施和广泛部署。为了解决这些问题，主要研究者(PI) 提出了一种称为可扩展核心（Scalable Core，简称 SCORE）的架构，其中网络被划分为连续的区域，称为岛。 在每个岛内，PI 区分边缘节点和核心节点。边缘节点执行按流管理，而核心节点则不执行。由于边缘节点管理的流量较少，并且边缘节点可以作为主机，因此该架构具有高度可扩展性。 主要目标是使用 SCORE 架构来近似参考岛，其中所有节点都执行每个流管理。通过这种方式，可以为各种资源管理策略提供有效的支持。为了近似参考网络，PI 引入了两种方案。在第一个方案中，每个入口节点在每个数据包进入网络时用它所属的流的状态（例如，速率）来标记每个数据包。此外，每个核心节点根据其标签和节点状态（例如利用率）来处理数据包。 在第二种方案中，流路径上所有节点的状态被聚合并发送给边缘节点。根据这些信息和流状态，边缘路由器决定如何处理传入数据包（例如，转发或丢弃它）。PI 计划在 SCORE 框架内开发一套集成算法，以支持尽力而为的拥塞控制服务、端到端QoS保证、差异化服务。 他将通过分析、模拟和实施相结合的方式进行研究。此外，他还计划在CAIRN高速测试床网络上进行规模化实验，并与行业合作伙伴（思科、Ascend、3Com、英特尔、MCI）合作，加快已开发技术向行业的过渡。 这项工作的结果预计将对互联网资源管理算法的设计产生重大影响。