Hardware support for reliable networking; from protocols to accelerators

这项研究计划的长期目标是获得可靠和有效的电子系统，预计在未来5年内将做出重大贡献。一些威胁和故障机制可能危及电子系统的可靠性，当这些系统提供正确的功能，同时提供足够的吞吐量、延迟、功耗和能耗时，这些系统是有效的。如果可靠性和有效性/效率可以是正交的问题，所提出的研究旨在为获得平衡和更好的系统做出贡献。人们越来越关注支持云服务的数据中心的可靠性和效率。关键问题源于链路数据速率的稳定增长（通常是40gb /s， 100gb /s正在出现，400gb /s和1tb /s即将出现）。随着速率的增长，处理数据包的时间缩短，必须解决两个可靠性问题：传输错误和分布式拒绝服务攻击（DDoS）。实际上，来自互联网对计算机系统的一个非常重要和普遍的威胁是DDoS。DDoS的目标是使计算机资源饱和，从而使合法用户无法使用它。该计划将首先提出协议和流量控制，以提高数据中心网络的可靠性。一个协议将支持链路级完整性检查和重传。然后，该程序将调查数据包功能和带宽使用之间的映射，以支持对DDoS的被动防御。此外，我们将设计和实现算法来支持此映射概念，以提供资源限制作为抵御DDoS的弹性防御。这些算法将在自然界中分布；否则，包过滤就是一个可攻击的服务。换句话说，防御的努力可能是如此之大，以至于集中在被攻击的服务上仍然可能压倒系统的其他部分。其结果将是，资源（即服务）将受到网络行为内在的DDoS攻击的保护。另一方面，这种防御不能区分合法流量和攻击流量，因此产生的节流将影响两种流量。我们建议进一步完善基于主成分分析和深度学习等技术的攻击检测和缓解防御机制。据我们所知，在文献中从未提出过提供被动防御基础设施。该计划还旨在通过协议和流量控制来提高数据中心网络的可靠性，并扩展这些协议以减轻网络攻击，并提出和验证有效检测网络攻击的方法。

The long-term goal of this research program, toward which significant contributions are expected over the next 5 years is to obtain reliable and effective electronic systems. Several threats and failure mechanisms can jeopardize reliability of electronic systems and these systems are effective when they provide the right functionality, while offering adequate throughput, latency, power dissipation and energy consumption. If reliability and effectiveness/efficiency can be orthogonal concerns, the proposed research aims at contributing to both to get balanced and better systems. A growing concern is the reliability and efficiency of datacenters that notably support cloud services. Key issues stem from to the steady growth of link data rates (commonly 40 Gb/s, 100 Gb/s emerging, 400 Gb/s and 1 Tb/s on the horizon). With growing rates, the time to process packets shrinks and two reliability issues must be tackled: transmission errors and distributed denial-of-service attacks (DDoS). Ineed, a very significant and pervasive threat to computer systems from the Internet is the DDoS. The goal of a DDoS is to saturate a computer resource thus making it unavailable to legitimate users. The proposed program will first propose protocols and flow control to improve datacenter network reliability. One protocol will support link level integrity checking and retransmission. The program will then investigate mappings between packet function and bandwidth usage to support passive defense against DDoS. Also, we will devise and implement algorithms to support this mapping concept to provide resource throttling as a resilient defense to protect against DDoS. These algorithms will be distributed in nature; otherwise, the filtering of packets would be an attackable service. In other words, the effort to defend could be so large that concentrating it at the attacked service could still overwhelm the rest of the system. The result will be that resources (i.e. services) will be protected against DDoS attacks intrinsically by the behavior of the network. On the other hand, this defense does not differentiate legitimate traffic from an attack thus the resulting throttling would impact both traffics. We propose to further improve the defense mechanisms with detection and mitigation of attacks based on techniques like principal components analysis and deep learning. To the best of our knowledge, providing a passive defense infrastructure against has never been proposed in the literature. The program will also aim at improving datacenter network reliability through protocols and flow control, and to extend these protocols to enable cyber attack mitigation, and to propose and validate means of effectively detecting cyber attacks.