Global networking
The Global Networking (GN) team is responsible for the design, development, build and operation of the networks that connect our data centers to our customers.
About the team
The Global Networking (GN) team is responsible for the design, development, build and operation of Google’s global network that every Google service, including the Google Cloud Platform, runs on. We develop cutting-edge networking technologies that allow Google's global WAN to be zero touch, builds out some of the largest scale Software Defined Networks (SDNs) infrastructure ever deployed (B4, Espresso), scales Google's global Content Delivery Networks (CDNs) that supports Google services, develops sophisticated software systems for network capacity forecasting, planning and optimization.
We continuously expand the reach of Google's network across the world laying new optical fibers and building hundreds of points of presence worldwide. This global footprint allows us to optimize the end-to-end speed and reliability of the traffic that we carry for our users and for Google Cloud customers, delivering optimal performance.
In doing all this, we develop and rely on the most advanced techniques in network hardware and software, traffic engineering, and network management to deliver unprecedented scale, availability and performance at industry leading cost points. Additionally, we are also advancing the state of the art in data analytics and machine learning to drive network efficiency and optimization at scale.
Google has a long history of fundamental research in networking, and we have recently engaged in a collaborative research effort with NSF and other industrial partners to launch a $40 million program in academic research for Resilient and Intelligent Next-Generation (NextG) Systems, or RINGS. In addition to funding, Google will offer expertise, research collaborations, infrastructure, and in-kind support for researchers and students as they advance knowledge and progress in the field. See our blog post for additional information.
Congestion control and traffic management
All networks are subject to congestion; we want to operate ours at high utilization levels while meeting strict performance objectives. We’re inventing new congestion avoidance protocols, and improving our global-scale, near-real-time, automated traffic engineering system. We’re building better ways to measure our networks, accurately and at scale, to drive our evaluation of congestion-control techniques, and as real-time input to automated traffic management.
We collect traffic statistics all around our network infrastructure to track performance, detect quickly unusual events, and compute SLA compliance. We rely on the most advanced data science techniques, machine learning in particular, to reduce the time it takes to detect and root cause events. We use predictive analytics to anticipate some types of problems and adjust our traffic engineering (e.g. traffic surge), or to plan capacity increase.
We’re building automated network management systems, enabling us to rapidly repair and improve our networks with little or no downtime. We’re using techniques such as formal modeling of network topologies and highly-available distributed systems, while working closely with Google’s network engineers and operators to implement automated workflows.
We work on developing and deploying cutting-edge optical solutions to scale cost-effectively and to increase network availability. These include new coherent transmission technologies, disaggregated line systems, high-capacity submarine wet plant, subsea switching technologies, transport SDN configurations, and sophisticated physical and logical layer design and optimization tools.
We’re developing new mechanisms for low-latency, CPU-efficient communication. We want our network switches and endpoints to implement novel packet-processing functions without compromising on cost or performance. We’re exploring hardware and software techniques for fast, flexible, safe packet processing, including onload, offload, RDMA, P4, and more.
To introduce network innovations into production as rapidly as possible, without compromising availability, we test our designs and implementations early, often, and extensively. We’re developing advanced software validation techniques, we embrace automation in all aspects of testing and qualification, and we build powerful infrastructure for testing, debugging, and root-causing, in both physical and emulated testbeds.
We employ SDN extensively. We were early users of, and contributors to, OpenFlow, and continue, with the P4 network processor programming language, to raise the level of abstraction for silicon-agnostic switching. We are developing SDN controller platforms that can handle Google’s needs for scale and reliability, and SDN applications for routing, traffic management, and other functions.
We’ve developed one of the world’s largest, most cost-effective wide area networks, and we continue to increase its scale and reliability, while extracting the best possible performance from WAN hardware and fiber links. We’re employing Google-designed and vendor hardware, SDN controllers, and global-scale automated traffic engineering to address these challenges.
Featured publications
Some of our locations
Some of our people
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Sam Burnett
- Networking
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Christophe Diot
- Data Mining and Modeling
- Networking
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Dennis Fetterly
- Distributed Systems and Parallel Computing
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Drago Goricanec
- Networking
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Bikash Koley
- Distributed Systems and Parallel Computing
- Networking
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Subhasree Mandal
- Networking
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Steve Padgett
- Hardware and Architecture
- Networking
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Pavlos Papageorge
- Networking
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Massimiliano Salsi
- Algorithms and Theory
- Networking
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Anees Shaikh
- Distributed Systems and Parallel Computing
- Networking
- Software Systems
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Rob Shakir
- Networking
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Vijay Vusirikala
- Networking
