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Research Statement Automated Network Diagnostics with Provenance

My research goal is to make networks and distributed systems more robust. An increasingly large portion of our daily life depends on our networks, including e-commerce, video conferencing, and many other examples. Unfortunately, network outages are quite common, and they can cause significant damage – for instance, Google and Amazon can lose tens of thousands of dollars for every minute of downtime. These problems happen due to at least two reasons. First, networks and distributed systems are difficult to get right, as they are complex and large in scale. Even major data centers are not immune to network misconfigurations, software bugs, or ill-planned service updates. Second, they are plagued by various attacks, which are getting more advanced and harder to defend against. Recently, the U.S. East Coast experienced a massive outage due to a distributed denial-of-service attack by compromised IoT devices. To avoid these problems, it is necessary to build more robust networks and distributed systems than those that are available today. My work addresses both of the above challenges. To diagnose non-malicious problems in networks and distributed systems, my thesis work takes an interdisciplinary approach that draws inspiration from the database community; it builds on, and substantially generalizes, the concept of data provenance to enable network diagnostics. To mitigate malicious attacks, I have designed techniques that can detect and diagnose timing anomalies that are caused by the attacker, and I have built systems that can guarantee a certain level of performance even when they are under attack. My core areas are distributed systems and networking. I have collaborated with academic researchers in systems, databases, networking, and security, as well as industrial researchers and engineers from Akamai Technologies, Microsoft Research, and Huawei Technologies. I believe that collaborations, particularly those across (sub)disciplines, are a fruitful avenue to innovation. I find research topics by identifying pain points in real-world network operations – for instance, I have identified common themes of reported problems in major network management forums, and I have conducted interviews with network operators and engineers from companies such as Microsoft, Comcast, and Google. As a systems researcher, I validate my research ideas by building concrete software prototypes; for network data-plane applications, I also rely on hardware prototypes, e.g., on FPGAs.