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Showing posts from November, 2018

HotNets'18: Networking in Space

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HotNets'18 was held at Microsoft Research, Building 99. This is walking distance to my office at Cosmos DB, where I am working at my sabbatical. So I got tempted and crushed this workshop for a couple sessions. And oh my God, am I happy I did it. The space session was particularly very interesting, and definitely worth writing about. My God, it is full of satellites! According to a 2018 estimate, there are 4,900 satellites in orbit , of which about 1,900 operational, while the rest have lived out their useful lives and become space debris. Approximately 500 operational satellites are in l ow-Earth orbit , 50 are in medium-Earth orbit (at 20,000 km), and the rest are in geostationary orbit (at 36,000 km) . The low earth orbit LEO satellites are not stationary and fast moving around the earth at 1.5 hour per rotation. We are talking about the lowest ring in this picture , where International Space Station (ISS) resides. Since LEO satellites are close to Earth, this make

My Emacs journey

This is a follow up to my "Master your tools" post . As an example of one of my tools, I talk about my Emacs use. I have been using Emacs for the last 20 years. At this point, I don't even know Emacs, my fingers do. If you ask me the shortcut for something, I will need to let my fingers do it and try to observe what they are doing. And sometimes ---as in the story of the caterpillar who forgets how to walk when asked to demonstrate it--- I forget about how to do something when I try to attempt it consciously. Four stages of competence: 4. Unconscious Competence (Right Intuition) 3. Conscious Competence (Right Analysis) 2. Conscious Incompetence (Wrong Analysis) 1. Unconscious Incompetence (Wrong Intuition) https://t.co/peAEUtkMZV pic.twitter.com/OxZ3WqreVa — Colby Serpađź’ˇ (@ColbySerpa) November 6, 2018   From text-editing to text-wrangling I have been learning Emacs at a glacial pace, but I think that worked for me better. I figured I can internalize so

Is Twitter causally-consistent?

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For the past 7-8 years, several research papers have used this example to motivate causal consistency. You must have read this example, right? Alice removes her boss from her friend list, and posts that on her feed that she is looking for a new job.  Tom removes his mom from the friend list, and posts his Spring Break photos. Well, being the empirical researchers we are, Aleksey and I wanted to put Twitter in to test for this scenario. On September 25, we performed this test. (I also have a video recording of this. But since I can't stand to hear myself talk in recordings, I am not posting it. I sound really weird, man.) I first blocked Aleksey on my Twitter account, and then tweeted that Aleksey drinks a lot of tea (it's true). When we checked Aleksey's timeline, we saw that his timeline indeed did not display my tweet. @alekseycharapko drinks way too much tea. — Murat Demirbas (@muratdemirbas) September 25, 2018 So, this was kind of an anticlimax. Tw

How to be a good machine learning product manager

There are a lot of interesting meetups at Seattle, and I try to attend one every couple weeks. Ruben Lozano Aguilera was the speaker for this meetup on Oct 17. Ruben is a product manager at Google Cloud, and before that he was a product manager at Amazon. What is ML? Programming transforms data + rules into answers. Machine learning turns data + answers into rules. When should you use ML? Use ML if the problem: handles complex logic scales up really fast requires specialized personalization adapts in real-time For example ML is a good fit for the "search" problem.  Search requires complex logic, for which it is not easy to develop rules.  It scales up really fast in terms of new keywords, combinations and content. It requires personalization depending on the context, and has some real-time adaptation component as well. Another important point is that the problem should have existing examples of actual answers. When you bootstrap from a good enough dataset

SDPaxos: Building efficient semi-decentralized geo-replicated state machines

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In the last decade, the Paxos protocol family grew with the addition of new categories. Rotating leader: Mencius Leaderless: EPaxos, Fast Paxos Paxos federations: Spanner , vertical Paxos  Dynamic key-leader: WPaxos   This paper, which appeared in SOCC 18, proposes SDPaxos which prescribes separating the control plane (single leader) from the replication plane (multiple leaders). SD in SDPaxos stands for "semi-decentralized". The motivation for this stems from the following observation. Single leader Paxos approach has a centralized leader and runs into performance bottleneck problems. On the other hand, the leaderless (or opportunistic multileader) approach is fully decentralized but suffers from the conflicting command problems. Taking a hybrid approach to capture the best of both worlds, SDPaxos makes the command-leaders to be decentralized (the closest replica can lead the command), but the ordering-leader (i.e., the sequencer) is still centralized/unique in t

An unexpected phone call at the elevator

Sometime ago, I was visiting an apartment block. This was a relatively new apartment block, I think less than 5 years old. I entered the elevator, and I heard "Hello, hello... Are you there?" booming from the speakers. This never happened to me before of course; elevators don't talk to me often. I thought maybe someone had pressed the call for help button, and left the elevator, and I can help sort this out. I said, "Hi, yes!" The voice continued saying: -"The reason I am calling you is because of your last energy bill". After a second of cognitive dissonance, I started laughing: -"Umm, I don't know what happened, but I am in an elevator now, and your voice is literally streaming from the elevator." The voice stopped for a brief couple of seconds, then continued explaining something about the bill, following the script he was given. -"Dude, this is my floor, and I got to go now. Ok, bye." It turns out most eleva

Judoing the Dunning-Kruger effect: the "surprisingly-popular option" strategy for crowdsourcing

Let's say you want to crowdsource the answer to the question: (Q1) What is the capital of Brazil? The surprisingly-popular option  strategy for crowdsourcing suggests piggybacking a control  question to the real question Q1: (Q2) What do you think the majority of other people will respond to this question? Many people (non-Brazilian and non-geography-nerds) will answer with Rio for both Q1 and Q2. But there will be some people that will answer with Brasilia for Q1 and yet Rio for Q2. The first set of people that replied with Rio to both questions did not know much about Brazil, and went with what they know as the most prominent city in Brazil. The second set of people not only knew of the correct answer, Brasilia, but they also anticipated that the majority of participants will go wrong by answering with Rio. Rio is the popular option for Q1, but Brasilia is the surprisingly popular option  because the respondents for Brasilia had anticipated that Rio would be the popular

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