ITR: Protocol Coordination for Multistream Applications

ITR：多流应用程序的协议协调

• 批准号: 0219780
• 负责人: Ketan Mayer-Patel
• 金额: --
• 依托单位: University of North Carolina at Chapel Hill
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2002
• 资助国家: 美国
• 起止时间: 2002-10-01 至 2007-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0219780&HistoricalAwards=false
• 关键词: ITR; Protocol; Coordination; Multistream; Applications

The world is rapidly being populated by a wide array of information appliances such as computers, personal digital assistants, video cameras, digital light projectors, and cable set-top boxes. Theseappliances are no longer simply islands of technology, but have the ability to communicate with other devices in their environment. Future Internet applications will increasingly make use of thesedevices by organizing them in a distributed fashion. Examples of these applications include distributed sensor arrays, tele-immersion, computer-supported collaborative workspaces (CSCW), ubiquitous computing environments, and complex multistream, multimedia presentations. In these applications, no one device or computational resource produces or manages all of the data streamstransmitted. Instead, these applications will be distributed over a collection of devices in an environment. These types of applications are called "cluster-to-cluster" (C-to-C) applications.In a C-to-C application, a set of processes distributed on a cluster of devices or computers communicates with another set of processes on a remote cluster of devices or computers. Processes are distributed on the device clusters at either end to manage the data streams and control the application. Unfortunately, traditional network technologies and protocols are ill-equipped to support these kinds of applications.The fundamental problem is that current transport-level protocols operate in isolation from other traffic flows and within a strict understanding of "end-to-end." The transport-level protocols used by multiple, related, data streams that share a common path have no coordination mechanism. As a result, each process in a C-to-C application competes with other processes within the same application for network resources. Also, each transport-level protocol must make independent assessments of current network conditions (e.g., delay, congestion, etc.) which can lead to inconsistent and adversarial protocol dynamics. Furthermore, the numerous data streams produced by a C-to-C application will have semantic relationships known only to the application. These relationships affect how the data should be transmitted and the operation of transport-level protocols. A C-to-C application needs a global view of performance across all of its flowsin order to make adaptations to dynamic network conditions. Independent adaptation of the separate flows uninformed of aggregate application performance is insufficient.A key characteristic of C-to-C applications is that a large portion of the communication path is shared among all data flows. Although no two data flows may share an entire end-to-end path, all data flows share the path between the two clusters. Furthermore, this shared common path is likely to be where network conditions vary the most and the source of congestion due to outside traffic. Exploiting this characteristic, our general approach to the problem is to introduce mechanisms at the points of aggregation for data streams in a cluster application that determine network conditions along the shared common path and provide a consistent and coordinated view of available network resources.Specifically, a major contribution of our work will be to introduce an additional protocol between the network level (IP) and the transport level (TCP, UDP, etc.). We call this protocol the "Coordination Protocol" (CP). This additional protocol will be used to communicate information between forwarding mechanisms within the cluster infrastructure on either end of the application. The information exchanged by these mechanisms is used to estimate the dynamic network conditions along the shared path (i.e., congestion, latency, jitter, etc.). Because a single mechanism is charged with estimating network conditions across all flows of a multistream application, all individual transport-level protocols involved in a C-to-C application receive a consistent and coordinated view of current network conditions. The application can then react to congestion, loss, and other network events in a manner that incorporates application-level knowledge and achieves global objectives.The major features of the researchers approach are: - Provides a consistent measurement of network conditions across all application flows. - Preserves end-to-end semantics of transport-level protocols. - Locally deployable. - Independence from application architecture. - Serves as a framework for other types of coordination.As a whole, the aggregate network behavior of all the flows of a C-to-C application should respond appropriately to congestion and other network conditions. How each individual stream responds,however, can only be determined at the application level because only the application has an understanding of how the streams are related. The coordination protocol we will develop provides cluster applications with the ability to apply application-level knowledge about these interstream semantic relationships and coordinate the use of network resources. The protocol will help us explore coordination mechanisms and make possible a wide range of new application typesthat do not currently exist, but are envisioned by researchers and industry as the future of the Internet.

世界上正迅速充斥着各种各样的信息设备，如计算机、个人数字助理、摄像机、数字投影仪和有线机顶盒。这些设备不再是简单的技术孤岛，而是具有与环境中的其他设备通信的能力。未来的互联网应用程序将越来越多地利用这些设备，将它们以分布式的方式组织起来。这些应用程序的例子包括分布式传感器阵列、远程沉浸、计算机支持的协作工作空间（CSCW）、无处不在的计算环境，以及复杂的多流、多媒体表示。在这些应用程序中，没有一个设备或计算资源产生或管理所有传输的数据流。相反，这些应用程序将分布在环境中的一组设备上。这些类型的应用程序称为“集群到集群”（C-to-C）应用程序。在C-to-C应用程序中，分布在设备或计算机集群上的一组进程与远程设备或计算机集群上的另一组进程通信。进程分布在两端的设备集群上，对数据流进行管理，对应用进行控制。不幸的是，传统的网络技术和协议无法支持这类应用程序。根本的问题是，当前的传输级协议与其他通信流是隔离的，并且严格地理解“端到端”。共享公共路径的多个相关数据流使用的传输级协议没有协调机制。因此，C-to-C应用程序中的每个进程与同一应用程序中的其他进程竞争网络资源。此外，每个传输级协议必须对当前网络状况（例如，延迟、拥塞等）进行独立评估，这可能导致不一致和对抗性的协议动态。此外，C-to-C应用程序产生的大量数据流将具有只有该应用程序才知道的语义关系。这些关系影响数据应该如何传输以及传输层协议的操作。C-to-C应用程序需要对其所有流的性能进行全局视图，以便适应动态网络条件。不了解总体应用程序性能的单独流的独立适应是不够的。C-to-C应用程序的一个关键特征是通信路径的很大一部分在所有数据流之间共享。尽管没有两个数据流可以共享整个端到端路径，但所有数据流都共享两个集群之间的路径。此外，这条共享的公共路径可能是网络条件变化最大的地方，也是由于外部流量造成的拥塞的来源。利用这个特性，我们解决这个问题的一般方法是在集群应用程序中的数据流的聚合点引入机制，这些机制确定沿着共享的公共路径的网络条件，并提供可用网络资源的一致和协调的视图。具体来说，我们工作的一个主要贡献将是在网络层（IP）和传输层（TCP、UDP等）之间引入一个额外的协议。我们把这个协议称为“协调协议”（CP）。此附加协议将用于在应用程序两端的集群基础设施内的转发机制之间通信信息。通过这些机制交换的信息用于估计共享路径上的动态网络状况（即拥塞、延迟、抖动等）。由于单一机制负责评估跨多流应用程序的所有流的网络状况，因此C-to-C应用程序中涉及的所有单独的传输层协议都接收到当前网络状况的一致和协调视图。然后，应用程序可以对拥塞、丢失和其他网络事件做出反应，并以结合应用程序级知识的方式实现全局目标。研究人员方法的主要特点是：-提供跨所有应用程序流的网络条件的一致测量。-保留传输级协议的端到端语义。—可本地部署。—独立于应用架构。-作为其他类型协调的框架。总的来说，C-to-C应用程序的所有流的聚合网络行为应该对拥塞和其他网络条件做出适当的响应。然而，每个单独的流如何响应只能在应用程序级别确定，因为只有应用程序了解流是如何相关的。我们将开发的协调协议为集群应用程序提供了应用有关这些流间语义关系的应用程序级知识和协调网络资源使用的能力。该协议将帮助我们探索协调机制，并使广泛的新应用类型成为可能，这些类型目前还不存在，但被研究人员和工业界设想为互联网的未来。