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This paper presents our experience in coordinating and teaching a novel graduate systems and computing course named 'Successful Systems in Production' (SSP). The course targets graduate students of different research interests in Computer Science. The course aims at giving a breadth knowledge on cutting-edge well-known systems in production, and exploring the potential synergies across different areas of research. Having its roots in Distributed Computing, SSP addresses those systems that overlap with other research areas like Computational Systems, Parallel Computing, Databases, Cloud Computing, Artificial Intelligence, Security, etc. SSP exhibits an agile topic selection model that fits several students' backgrounds in each academic year. The topics focus on the practical aspects of each selected system that is considered 'successful', i.e., based on its worldwide impact and technical significance. This is important for graduate students to acquire best practices in industry and academia, necessary to build practical computing systems. In the same vein, the assessment method includes a project that is based on one of the presented systems and also intersects with the student's own research plan. Based on our teaching experience and the excellent feedback of the students, we strongly recommend this graduate course to be taught at other universities. © 2019 IEEE.

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Cryptocurrency and blockchain technologies are recently gaining wide adoption since the introduction of Bitcoin, being distributed, authority-free, and secure. Proof of Work (PoW) is at the heart of blockchain's security, asset generation, and maintenance. Although simple and secure, a hash-based PoW like Bitcoin's puzzle is often referred to as “useless”, and the used intensive computations are considered “waste” of energy. A myriad of Proof of “something” alternatives have been proposed to mitigate energy consumption; however, they either introduced new security threats and limitations, or the “work” remained far from being really “useful”. In this work, we introduce Proof of eXercise (PoX): a sustainable alternative to PoW where an eXercise is a real world matrix-based scientific computation problem. We provide a novel study of the properties of Bitcoin's PoW, the challenges of a more “rational” solution as PoX, and we suggest a comprehensive approach for PoX. © 2018 Copyright held by the owner/author(s).

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Eventual consistency (EC) is a relaxed data consistency model that, driven by the CAP theorem, trades prompt consistency for high availability. Although, this model has shown to be promising and greatly adopted by industry, the state of the art only assumes that replicas can crash and recover. However, a Byzantine replica (i.e., arbitrary or malicious) can hamper the eventual convergence of replicas to a global consistent state, thus compromising the entire service. Classical BFT state machine replication protocols cannot solve this problem due to the blocking nature of consensus, something at odd with the availability via replica divergence in the EC model. In this work in progress paper, we introduce a new secure highly available protocol for the EC model that assumes a fraction of replicas and any client can be Byzantine. To respect the essence of EC, the protocol gives priority to high availability, and thus Byzantine detection is performed off the critical path on a consistent data offset. The paper concisely explains the protocol and discusses its feasibility. We aim at presenting a more comprehensive and empirical study in the future. © 2017 ACM.

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