Clock synchronization: https://www.usenix.org/conference/nsdi18/presentation/geng
I think the TechCrunch article doesn't really explain their application of clock synchronization well. Here are the other relevant papers and my attempt at explaining the general idea below.
Network edge-based measurement (one-way delay?): https://www.usenix.org/system/files/nsdi19-geng.pdf
Congestion Control: https://www.usenix.org/system/files/nsdi21-liu.pdf
Each paper I've listed builds on the last. Their method to synchronize clocks made accurate and efficient measurement of one-way delay possible with commodity hardware. This measurement of one-way delay occurs at the edge, allowing them to "hold" incoming packets at the edge for extremely small periods to reduce congestion (latency) while maintaining throughput. From my understanding, traditional congestion control algorithms require rich telemetry from the entire network, which is likely not accessible in a public cloud environment. Balaji and clockwork's algorithms only need to make these measurements from the edge (which customers in public cloud have access to).
I'm curious to see how all this will scale for multi-region deployments. If the latency between VMs from region 1 and region 2 is significant, I wonder if the measurement will actually be useful in deciding to "hold" the packets.
Accurate clocks sync enables true one-way delay measurements (instead of RTT/2), this allows for edge-based network visibility. We launched Latency Sensei beta – a sensor, monitor and auditor that provides visibility into cloud deployments. The gallery has cloud fitness reports on GCP, AWS and Azure. Some interesting reports include: 1)how VM colocation impairs network bandwidth, and 2) tale of 2 cloud regions, London vs Singapore. Take a look and we'd love to get some feedback https://sensei.clockwork.io/user/gallery/
On Congestion control, an edge-based solution is coming soon. If you're interested in a private beta, email us at [email protected]
The first article you reference includes something about Support Vector Machines (SVMs).
They have the 'names' because they are a reputable group of people. They have been at this problem for a while, first with extensive research that required clock sync as a pre-requisite, and then to evolving into clock sync as a formidable problem unto itself.
Clockwork is a rename of the company as far as I can tell. Their original name (Tick Tock Networks) [1] was probably too close to what has become a very popular homophone.
You seem to know their work, so if you have further publications, I’d love to get them please.
Haven't watched this one, but might be complementary: https://www.youtube.com/watch?v=Opf9CBwP5R8.
Juicero raised $120M.
Just some words:
Theranos.
Ubeam.
Moller.
And many, many others. Investors do this all the time. FOMO + 'wouldn't it be nice' are powerful ways to part fools from their money.
You’d be surprised, I was.
The figures (eg $21M) and names dropped (eg Stanford) are an appeal to authority, which does make me curious.
I’d love to see some papers, I went through all of Balaji Prabhakar‘s publications (titles only), and didn’t see a single paper that sounded like “NTP but machine learning.
If anyone else knows more about this, I’d love to hear from you. Surely $21M doesn’t get dropped with at least someone doing due dill on the tech?