CC*DNI Integration: Enhancing Science Through Custom Paths For Trusted Users

CC*DNI 集成：通过受信任用户的自定义路径增强科学

基本信息

批准号：
1541426
负责人：
James Griffioen
金额：
$ 99.93万
依托单位：
University of Kentucky Research Foundation
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2015
资助国家：
美国
起止时间：
2015-09-01 至 2019-08-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1541426&HistoricalAwards=false
关键词：
CC DNI Integration Enhancing Science

项目摘要

Progress in medicine, science, and engineering -- as in essentially all areas of human endeavor -- increasingly depends on network access to very large data sets (billions to trillions of bytes) containing information such as scientific measurements, monitoring information, images, videos, simulation results, etc. The number of researchers working with, transferring, and sharing very large data sets is growing at an alarming rate. Although network transmission speeds are rapidly increasing, devices deployed in the middle of the network for security and management purposes -- e.g., firewalls, intrusion detectors, and the like -- create major bottlenecks that prevent researchers from being able to quickly move these large files between laboratories, high-performance computing sites, and storage facilities.Historically, network designers have addressed this problem by creating and maintaining a special "Science DMZ" network that provided a "fast lane", bypassing performance-limiting security devices thanks to the trusted nature of the users and applications connected to the Science DMZ. Today, however, the growing number and variety of users who need high-performance data transfer makes it increasingly difficult to maintain such a separate infrastructure. This project is developing ways to provide trusted users on the normal (campus) network with dynamic access to such fast lanes by authenticating them on-the-fly, determining the nature of their data transfer, and whether it should be allowed or not.This project leverages emerging Software-Defined Networking (SDN) capabilities to single out individual data flows for specialized treatment in the network. Using the SDN infrastructure already deployed on campus, the project is developing new control software and protocols that enable trusted users to authenticate themselves to the network and set up network connections free from middlebox interference while still enforcing middlebox security functionality for normal campus traffic. The ability of trusted users to create such fast lanes -- as opposed to (only) network administrators -- will enable future networks to handle the rapidly growing number of big data users.

医学、科学和工程领域的进步——基本上就像人类努力的所有领域一样——越来越依赖于网络访问非常大的数据集（数十亿到数万亿字节），其中包含科学测量、监测信息、图像、视频等信息、模拟结果等。处理、传输和共享非常大的数据集的研究人员数量正在以惊人的速度增长。尽管网络传输速度正在迅速提高，但出于安全和管理目的而部署在网络中间的设备（例如防火墙、入侵检测器等）造成了主要瓶颈，阻碍了研究人员快速移动这些大文件实验室、高性能计算站点和存储设施之间。从历史上看，网络设计人员通过创建和维护一个特殊的“科学 DMZ”网络来解决这个问题，该网络提供了“快车道”，绕过性能限制的安全设备，这要归功于可信的的性质连接到 Science DMZ 的用户和应用程序。然而，如今，需要高性能数据传输的用户数量和种类不断增加，使得维护这种独立的基础设施变得越来越困难。该项目正在开发方法，通过动态验证用户身份，确定其数据传输的性质以及是否应允许，为普通（校园）网络上的可信用户提供对此类快速通道的动态访问。该项目利用新兴的软件定义网络 (SDN) 功能来挑选出单独的数据流，以便在网络中进行专门处理。该项目正在利用园区内已部署的 SDN 基础设施开发新的控制软件和协议，使受信任的用户能够向网络验证自己的身份，并建立不受中间件干扰的网络连接，同时仍对正常园区流量实施中间件安全功能。受信任的用户（而不是（仅）网络管理员）创建此类快速通道的能力将使未来的网络能够处理快速增长的大数据用户数量。

项目成果

期刊论文数量（3）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Navigating the Unexpected Realities of Big Data Transfers in a Cloud-based World

在基于云的世界中应对大数据传输的意外现实

DOI：
10.1145/3219104.3229276
发表时间：
2018-07
期刊：
PEARC '18 Proceedings of the Practice and Experience on Advanced Research Computing
影响因子：
0
作者：
Rivera, Sergio;Griffioen, James;Fei, Zongming;Hayashida, Mami;Shi, Pinyi;Chitre, Bhushan;Chappell, Jacob;Song, Yongwook;Pike, Lowell;Carpenter, Charles;et al
通讯作者：
et al

Debugging SDN in HPC Environments

在 HPC 环境中调试 SDN

DOI：
10.1145/3219104.3229277
发表时间：
2018-07
期刊：
PEARC '18 Proceedings of the Practice and Experience on Advanced Research Computing
影响因子：
0
作者：
Hayashida, Mami;Rivera, Sergio;Griffioen, James;Fei, Zongming;Song, Yongwook
通讯作者：
Song, Yongwook

Dynamically Creating Custom SDN High-Speed Network Paths for Big Data Science Flows

为大数据科学流程动态创建自定义 SDN 高速网络路径