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impact (n) 1. the action of one object coming forcibly into contact with another 2. the effect or influence of one person, thing, or action, on another Impact (with the second meaning :-) is an often talked about desirable thing in academic and research world. Impact is especially important for promoting an associate professor to a full professor status. Unfortunately there is no well-defined description or an objective way to quantify impact. There are approximated metrics, each with significant flaws: Citation count is easily quantifiable --Google Scholar shows your citation count and h-index. However, this can be tricked. Some journals have boosted their impact factors by asking accepted articles to cite other articles from the journal. Publishing in popular/crowded areas (e.g., wireless networks) can also boost citation count. It is possible to have high citation count with little impact, and little citation count with high impact. As a personal anectode, many of the work I

This is a half-baked exploratory piece about how some self-stabilization ideas may relate with blockchain consensus in open/permissionless environments. I will write about some similarities and some major differences between the self-stabilizing distributed algorithms work and blockchain consensus deployments. Self-stabilization Let's start with a brief review self-stabilization . Stabilization is a type of fault-tolerance that handles faults in a principled unified manner instead of on a case-by-case basis. Instead of trying to figure out how much faults can disrupt the system's operation, stabilization assumes arbitrary state corruption, which covers all possible worst-case collusions of faults and program actions. Stabilization then advocates designing recovery actions that takes the program back to invariant states starting from any arbitrary state. This makes stabilization suitable for dealing with unanticipated faults. The most distinct property of self-stabilizat

I didn't know what to expect when I picked this book from the library. A book by an astronaut could turn out to be boring and mundane for me. The thing is, I am interested in space, but I wouldn't say I am passionate about it. I never wished I could be an astronaut as a child (or as an adult). I guess I wanted to be the engineer that designed those systems, rather than the astronaut that piloted them. Long story short, I enjoyed reading this book a lot. I never got bored, on the contrary I was very engaged. The book interleaved Scott Kelly 's growing up and his 1 year stay at the International Space Station (ISS) at every other chapter. At the end of the book, Scott's life timeline has caught up to the beginning of his year-long ISS stay, and his ISS stay timeline concluded with the Soyuz return capsule entering the atmosphere. I learned a lot about the space program. It still weirds me out that while we are very much earth-bound with our lives, technology, perspect

This paper is by Team-Rocket ---the authors are pseudonymous, I presume a guy, a gal, and a cat is involved. I learned about the paper when Emin Gun Sirer announced it on Twitter. Here is the synopsis from the paper. "This paper introduces a brand new family of consensus protocols suitable for cryptocurrencies, based on randomized sampling and metastable decision. The protocols provide a strong probabilistic safety guarantee, and a guarantee of liveness for correct clients." Below I first summarize the protocols and at the end I will provide my comments/evaluations. The analysis of the paper is very strong and span 8 pages, but I skip that section in my review. Introduction Traditional consensus protocols incur high communication overhead and accurate knowledge of membership. So while they work great for less than 20 participants, they do not work for large numbers of participants and open/permissionless environments. Nakamoto consensus family protocols address tha