Publications
Our teams aspire to make discoveries that impact everyone, and core to our approach is sharing our research and tools to fuel progress in the field.
Our teams aspire to make discoveries that impact everyone, and core to our approach is sharing our research and tools to fuel progress in the field.
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1 - 15 of 328 publications
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Despite the advent of legislation such as the General Data Protection Regulation (GDPR) with its associated "Right to be Forgotten" (RTBF), few, if any, studies have measured user reactions to realistic edge cases with public-interest content. Surveying both users covered by and excluded from RTBF, this vignette-based survey experiment sought to better understand how users think of delisting content from search engine results and what factors influence user perceptions. While leaving information accessible in search engine results generally leads to warmer feelings towards those search engines than delisting it, we find that users do prefer different outcomes
depending on contextual elements specific to given cases. We also find that whether a country has active RTBF legislation does seem to be associated with both knowledge and attitudes about RTBF, but is unlikely to explain all of it. These results indicate a complex context around removing public-interest content from search engines’ results; it is essential that experts sensitive to local context perform the review in order to ensure that removal requests are handled in a way that meets users’ expectations.
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Record Number of Members Visit U.S. Congress to Talk Tech Policy
IEEE Spectrum (2025)
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This IEEE Spectrum article reflects on advocacy for U.S. technological leadership during my Congressional visit through IEEE-USA. Leading an expert group of other distinguished IEEE members, we urged lawmakers to support critical initiatives. Key priorities included sustained funding for federal research institutions like NIST, NASA, and the NSF, reauthorizing the SBIR/STTR programs vital for small business innovation, and passing the CREATE AI Act to democratize AI resources by establishing the National AI Research Resource (NAIRR).
We also emphasized strengthening the STEM talent pipeline through the CHIPS and Science Act and expanding high-skilled immigrant visas. We highlighted rapid AI advancements, such as autonomous vehicles, the surge in FDA-approved AI based medical devices, as underscoring the need for these strategic investments and policy actions. The article conveys a sense of urgency, calling for concrete congressional action to ensure the U.S. maintains its technological edge while also sharing my personal experiences.
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Probe-Based Study of Traffic Variability for the Design of Traffic Light Plans
Eliav Buchnik
Shai Ferster
Tom Kalvari
Dan Karliner
Omer Litov
Nitzan Tur
Danny Veikherman
Jack Haddad
COMSNETS 2024, https://www.comsnets.org/ (2024)
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Computing efficient traffic signal plans is often based on the amount of traffic in an intersection, its distribution over the various intersection movements and hours as well as on performance metrics such as traffic delay. In their simple and typical form, plans are fixed in the same hour over weekdays. This allows low operation costs without the necessity for traffic detection and monitoring tools. A critical factor in the potential efficiency of such plans is the similarity of traffic patterns over the days along each of the intersection movements. In this paper, we study traffic variability and propose simple metrics to measure it based on traffic volume and traffic delay. We propose an automatic probe data-based method, for city-wide estimation of traffic variability. We discuss how such measures can be used for signal planning such as an indication of which intersections can benefit from dynamic but expensive traffic detection tools or in selecting plan resolution. Likewise, we discuss various methods to mitigate the impact of such variability. We demonstrate the framework based on real traffic statistics to study the traffic variability in the city of Haifa along its 162 intersections.
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On the Benefits of Traffic “Reprofiling” The Single Hop Case
Henry Sariowan
Jiaming Qiu
Jiayi Song
Roch Guerin
IEEE/ACM Transactions on Networking (2024)
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Datacenters have become a significant source of traffic, much of which is carried over private networks. The operators of those networks commonly have access to detailed traffic profiles and performance goals, which they seek to meet as efficiently as possible. Of interest are solutions that guarantee latency while minimizing network bandwidth. The paper explores a basic building block towards realizing such solutions, namely, a single hop configuration. The main results are in the form of optimal solutions for meeting local deadlines under schedulers of varying complexity and therefore cost. The results demonstrate how judiciously modifying flows’ traffic profiles, i.e., reprofiling them, can help simple schedulers reduce the bandwidth they require, often performing nearly as well as more complex ones.
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This is an invited OFC 2024 conference workshop talk regarding a new type of lower-power datacenter optics design choice: linear pluggable optics. In this talk I will discuss the fundamental performance constraints facing linear pluggable optics and their implications on DCN and ML use cases
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KATch: A Fast Symbolic Verifier for NetKAT
Mark Moeller
Jules Jacobs
Olivier Savary Belanger
David Darais
Cole Schlesinger
Nate Foster
Alexandra Silva
Programming Languages and Implementation (PLDI) (2024) (to appear)
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We develop new data structures and algorithms for checking verification queries in NetKAT, a domain-specific language for specifying the behavior of network data planes. Our results extend the techniques obtained in prior work on symbolic automata and provide a framework for building efficient and scalable verification tools. We present \KATch, an implementation of these ideas in Scala, including extended logical operators that are useful for expressing network-wide specifications and optimizations that construct a bisimulation quickly or generate a counter-example showing that none exists. We evaluate the performance of our implementation on real-world and synthetic benchmarks, verifying properties such as reachability and slice isolation, typically returning a result in well under a second, which is orders of magnitude faster than previous approaches.
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On the Benefits of Traffic “Reprofiling” The Multiple Hops Case – Part I
Henry Sariowan
Jiaming Qiu
Jiayi Song
Roch Guerin
IEEE/ACM Transactions on Networking (2024)
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Abstract—This paper considers networks where user traffic is regulated through deterministic traffic profiles, e.g. token buckets, and requirescleanguaranteed hard delay bounds. The network’s goal is to minimize the resources it needs to meet those cleanrequirementsbounds. The paper explores how reprofiling, i.e. proactively modifying how user traffic enters the network, can be of benefit. Reprofiling produces “smoother” flows but introduces an up-front access delay that forces tighter network delays. The paper explores this trade-off and demonstrates that, unlike what holds in the single-hop case, reprofiling can be of benefit even when “optimal”cleansophisticated schedulers are available at each hop.
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A Decentralized SDN Architecture for the WAN
Nitika Saran
Ashok Narayanan
Sylvia Ratnasamy
Ankit Singla
Hakim Weatherspoon
2024 ACM Special Interest Group on Data Communication (SIGCOMM) (2024)
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Motivated by our experiences operating a global WAN, we argue that SDN’s reliance on infrastructure external to the data plane has significantly complicated the challenge of maintaining high availability. We propose a new decentralized SDN (dSDN) architecture in which SDN control logic instead runs within routers, eliminating the control plane’s reliance on external infrastructure and restoring fate sharing between control and data planes.
We present dSDN as a simpler approach to realizing the benefits of SDN in the WAN. Despite its much simpler design, we show that dSDN is practical from an implementation viewpoint, and outperforms centralized SDN in terms of routing convergence and SLO impact.
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Ubiquitous and Low-Cost Generation of Elevation Pseudo Ground Control Points
Etienne Le Grand
Moustafa Youssef
14th International Conference on Indoor Positioning and Indoor Navigation (IPIN). Hong Kong, China, 2024.
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In this paper, we design a system to generate Pseudo Ground Control Points (PGCPs) using standard low-cost widely available GNSS receivers in a crowd-sourcing manner. We propose a number of GNSS points filters that removes different causes of errors and biases, and design a linear regression height estimator leading to high-accuracy PGCP elevations. Evaluation of our system shows that the PGCPs can achieve a median accuracy of 22.5 cm in 25 metropolitan areas in the USA.
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Distributed Tracing for InterPlanetary File System
Marshall David Miller
Rachel Han
Haorui Guo
2024 International Symposium on Parallel Computing and Distributed Systems (PCDS), IEEE, pp. 1-5
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The InterPlanetary File System (IPFS) is on its way to becoming the backbone of the next generation of the web. However, it suffers from several performance bottlenecks, particularly on the content retrieval path, which are often difficult to debug. This is because content retrieval involves multiple peers on the decentralized network and the issue could lie anywhere in the network. Traditional debugging tools are insufficient to help web developers who face the challenge of slow loading websites and detrimental user experience. This limits the adoption and future scalability of IPFS.
In this paper, we aim to gain valuable insights into how content retrieval requests propagate within the IPFS network as well as identify potential performance bottlenecks which could lead to opportunities for improvement. We propose a custom tracing framework that generates and manages traces for crucial events that take place on each peer during content retrieval. The framework leverages event semantics to build a timeline of each protocol involved in the retrieval, helping developers pinpoint problems. Additionally, it is resilient to malicious behaviors of the peers in the decentralized environment.
We have implemented this framework on top of an existing IPFS implementation written in Java called Nabu. Our evaluation shows that the framework can identify network delays and issues with each peer involved in content retrieval requests at a very low overhead.
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(Invited) How Traffic Analytics Shapes Traffic Engineering, Topology Engineering, and Capacity Planning of Jupiter
Jianan Zhang
Optical Fiber Communication (OFC) Conference, IEEE (2023)
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Three prominent traffic features including peak alignment, stable ranking, and gravity model, have guided the design of current Google Jupiter fabrics in traffic engineering, topology engineering, and capacity planning.
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Change Management in Physical Network Lifecycle Automation
Virginia Beauregard
Kevin Grant
Angus Griffith
Jahangir Hasan
Chen Huang
Quan Leng
Jiayao Li
Alexander Lin
Zhoutao Liu
Ahmed Mansy
Bill Martinusen
Nikil Mehta
Andrew Narver
Anshul Nigham
Melanie Obenberger
Sean Smith
Kurt Steinkraus
Sheng Sun
Edward Thiele
Proc. 2023 USENIX Annual Technical Conference (USENIX ATC 23)
Preview abstract
Automated management of a physical network's lifecycle is critical for large networks. At Google, we manage network design, construction, evolution, and management via multiple automated systems. In our experience, one of the primary challenges is to reliably and efficiently manage change in this domain -- additions of new hardware and connectivity, planning and sequencing of topology mutations, introduction of new architectures, new software systems and fixes to old ones, etc.
We especially have learned the importance of supporting multiple kinds of change in parallel without conflicts or mistakes (which cause outages) while also maintaining parallelism between different teams and between different processes. We now know that this requires automated support.
This paper describes some of our network lifecycle goals, the automation we have developed to meet those goals, and the change-management challenges we encountered. We then discuss in detail our approaches to several specific kinds of change
management:
(1) managing conflicts between multiple operations on the same network;
(2) managing conflicts between operations spanning the boundaries between networks;
(3) managing representational changes in the models that drive our automated systems.
These approaches combine both novel software systems and software-engineering practices.
While this paper reports on our experience with large-scale datacenter network infrastructures, we are also applying the same tools and practices in several adjacent domains, such as the management of WAN systems, of machines, and of datacenter physical designs. Our approaches are likely to be useful at smaller scales, too.
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We introduce logical synchrony, a framework that allows distributed computing to be coordinated as tightly as with pure synchrony without the distribution of a global clock or any reference to a universal time. We describe and prove the main properties of the framework and point to how processes can be executed on a logically synchronous system.
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CAPA: An Architecture For Operating Cluster Networks With High Availability
Bingzhe Liu
Mukarram Tariq
Omid Alipourfard
Rich Alimi
Deepak Arulkannan
Virginia Beauregard
Patrick Conner
Brighten Godfrey
Xander Lin
Mayur Patel
Joon Ong
Amr Sabaa
Alex Smirnov
Manish Verma
Prerepa Viswanadham
Google, Google, 1600 Amphitheatre Pkwy, Mountain View, CA 94043 (2023)
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Management operations are a major source of outages for networks. A number of best practices designed to reduce and mitigate such outages are well known, but their enforcement has been challenging, leaving the network vulnerable to inadvertent mistakes and gaps which repeatedly result in outages. We present our experiences with CAPA, Google’s “containment and prevention architecture” for regulating management operations on our cluster networking fleet. Our goal with CAPA is to limit the systems where strict adherence to best practices is required, so that availability of the network is not dependent on the good intentions of every engineer and operator. We enumerate the features of CAPA which we have found to be necessary to effectively enforce best practices within a thin “regulation“ layer. We evaluate CAPA based on case studies of outages prevented, counterfactual analysis of past incidents, and known limitations. Management-plane-related outages have substantially reduced both in frequency and severity, with a 82% reduction in cumulative duration of incidents normalized to fleet size over five years
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Bolt is a congestion-control algorithm designed to providesingle-digit microsecond tail network-queuing at near-linerate utilization. Motivated by the need for ultra-low latencyto support applications such as NVMe, as line rates reach200G and beyond, most transfers fit within a single BDP en-tailing that transfer times predominantly become a functionof queuing and propagation delays. Bolt is an attempt topush congestion-control to its theoretical limits by harness-ing the power of programmable dataplanes such as Tofinoand Trident3+ chips. Bolt is founded on three key ideas, (i)Sub-RTT reaction (SRR): reacting to congestion faster thanRTT control-loop delay, (ii) Proactive Ramp-up (PRU): bytracking future flow-completions, and (iii) Supply matching(SM): leveraging Network Calculus concepts to maximizeutilization. Our current results achieve a 75% reduction inqueuing-delays over Swift with upto 3x improvement incompletion times for short transfers.
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