Diamond: Automating Data Management and Storage for Wide-Area, Reactive Applications

In their paper, Zhang proposed Diamond, which is a framework for reactive applications. A reactive application requires data consistency across clients. Traditional approaches such as notification servers or wide-area storage system are either slow or not fault-tolerant. To ease the pain of reactive application development, Zhan designed and implemented Diamond, which focuses on model and controller in the software MVC model. Diamond consists of the diamond cloud and the diamond client.

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Prochlo Strong privacy for analytics in the crowd

Today system analytics is critical for software development. For example, to gauge API adoption and find APIs to deprecate. Note that there could be millions of applications and thousands of APIs. Usually these data are collected into centralized databases on which various analytics are carried out. But these data may contain highly private information. The problem is how to handle the privacy data carefully?

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Pung: Unobservable communication over fully untrusted infrastructure

In their paper from 2016, Angel & Setty present Pung, a PIR-based messaging system that exploits clever data structure organization to amortize the traditionally high cost of computational private information retrieval to enable metadata-free communication without trusted parties. The primary contribution of the paper is the realization that a combination of bucketing and batch coding techniques would allow users to retrieve multiple messages in a single request with sub-linear costs the majority of the time. Its iterative optimizations to the naive C-PIR design that puts it closer in throughput to mixnet systems while offering lower latency and stronger privacy guarantees.

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Map Reduce

This paper talks about Map Reduce a programming paradigm by Google. Map Reduce is one of the most important distributed systems paper in the last few years. The authors Sanjay Ghemawat and Jefferey Dean are also present in other important systems paper of Google such as BigTable, GFS and TensorFlow.

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REM - Resource-Efficient Mining for Blockchains

Blockchain is a promising technology that can solve many problems. Nowadays, many of blockchains rely on Proof-of-Work(PoW) to produce new blocks which really waste lots of computational resources. In order to solve this problem, this paper presents REM(Resource-Efficient Mining) which is a new mining framework that uses Intel SGX. Their consensus method is called Proof-of-Useful-Work(PoUW). In this system, miners can use their CPUs for desired workload and contribute their work towards securing a blockchain as well.

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Scaling a file system to many cores using an operation log

This paper describes ScaleFS, a file system centered around the Scalable Commutativity Rule. An important contribution of this paper is to completely decouple the in-memory file system from the on-disk file system in order to scale out in the presence of multiple cores. File systems like Linux’s ext4 suffer from the problem that two commutative operations on the same directory contend for cache lines thereby directly impacting the scalability in multi-core systems.

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Light-Weight Contexts: An OS Abstraction for Safety and Performance

When designing a system where performance is the main priority, it is often the case where security is over looked. Motivated by the Heartbleed incident in 2014, authors of this paper realized that there needs to be a light weight isolation mechanism that the applications such as high performance webservers can use so that each session have a different view of the memory. Therefore, they proposed a lwC that will do just that: a light weight container that can contain certain parts of the process execution.

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Quantum Operating Systems

In the post, we are discussing “Corrigan-Gibbs, H., Wu, D. J., & Boneh, D. (2017, May). Quantum operating systems. In Proceedings of the 16th Workshop on Hot Topics in Operating Systems (pp. 76-81). ACM.”.

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