NetSE: Small: Network Memory for the Future Internet

包括pi在内的几项研究已经推断出互联网流量内容中存在相当数量的冗余（高达99%）。这些研究清楚地表明，通过适当地利用冗余，可以极大地提高通信性能。在本研究中，研究者研究并开发了一个面向未来互联网的网络存储器解决方案。网络内存的最简单形式是在每个网络元素上都有一个允许存储/检索操作的内存。当特定数据第一次流经元素时使用存储操作。当稍后需要从该元素检索相同的数据时，将使用检索操作。使用这种网络内存的主要目标是在将任何内容从服务器传送到任何客户机时，尽量减少或消除任何冗余流量，从而减少带宽需求。智力优势：由内容服务器、路由器和客户端组成的Internet的底层结构很少（如果有的话）执行记忆，因此对记忆的内容进行重用。本研究的重点是重新思考互联网的这一方面，以设计未来的互联网架构。研究人员将网络内存作为未来互联网的新3.5层引入，它位于传输层之下，网络层之上。使用网络内存的总体好处是通过利用冗余获得更好的网络交付性能和更高的网络利用率。以前的技术，如web缓存、cdn和P2P应用程序，虽然原则上试图利用冗余，但要么没有利用可用的冗余，要么范围太窄，甚至无法尝试利用各种（时间和空间）维度上的冗余。研究者计划通过工作解决的问题子集包括：1。数据在网络内存中的存储粒度是多少？应该是子包级、包级还是超级包级粒度？2. 谁是网络内存的参与者？是客户机、内容服务器、路由器，还是所有这些？3. 网络内存是如何工作的？如何确定内存位置为任何给定的数据？网络内存的寻址是如何执行的？4. 网络内存是否应该支持复杂的操作，而不仅仅是存储和检索？研究人员还将探讨网络内存的基本问题，如流量冗余的性质和网络压缩的概念。最后，本研究将讨论与网路记忆体相关的几个关键系统问题，包括实现开销、协议与报头格式，以及对其他网际网路协议的影响。更广泛的影响：除了研究生和本科生的培训机会外，该研究还将针对网络存储层解决方案的标准化和技术转移。更广泛的影响还包括：(a)通过pi教授的高级本科课程发展本科课程，(b)通过pi教授的两个关于网络和信息理论的研究生课程发展研究生课程，(c)支持少数民族学生。

Several studies including those by the PIs have inferred the presence of considerable amounts of redundancy in Internet traffic content (ranging up to 99%). These studies clearly establish the tremendous scope for enhancing communication performance through appropriate exploitation of the redundancies. In this research, the investigators study and develop a network memory solution for the future Internet. Network memory, in its simplest form, involves a memory at every network element that allows store/retrieve operations. The store operation is used when a particular data flows through the element for the first time. The retrieve operation is used when the same data needs to be retrieved from that element at a later point. The primary goal of using such a network memory is to minimize or eliminate any redundant traffic when delivering any content from its server to any client, and hence, reducing the bandwidth requirements. Intellectual Merit: The underlying fabric of the Internet consisting of the content Servers, routers, and clients perform very little, if any, memorization and hence re-use of the memorized content. The focus of this research is to rethink this aspect of the Internet for the design of the future Internet architecture. The investigators introduce network memory as a new layer 3.5 for the future Internet, residing beneath the transport layer and above the network layer. The overall benefits of using network memory are better network delivery performance and higher network utilization levels through the exploitation of redundancies. Previous techniques such as web-caching, CDNs, and P2P applications, while in principle try to leverage redundancy, either do not harness the redundancy available or are too narrow in their scope to even attempt leveraging redundancies along the various (temporal and spatial) dimensions. A subset of the questions that the investigators plan to address through the work includes: 1. What is the granularity at which data should be memorized in the network memory? Should it be sub-packet, packet-level, or even super-packet level granularity? 2. Who are the participants in the network memory? Is it the clients, content-servers, or routers, or perhaps all of them? 3. How does the network memory work? How is the memory location determined for any given data? How is addressing of the network memory performed? 4. Should the network memory support sophisticated operations beyond just store and retrieve? The investigators will also explore fundamental issues with the network memory such as the nature of traffic redundancies and the concept of network compression. Finally, the research will address several key systems issues pertaining to the network memory including overheads of realization, protocol and header formats, and impact on other Internet protocols. Broader Impact: In addition to graduate and undergraduate training opportunities, the research will be aimed at the standardization and technology transfer for the network-memory-layer solutions. The broader impact also includes: (a) Undergraduate curriculum development through senior undergraduate classes taught by the PIs, (b) Graduate curriculum development through two graduate-level classes on networking and information theory taught by the PIs, (c) Support for minority students.