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Events in distributed systems include sending or receiving messages, or changing some state in a node. Not all events are related, but some events can cause and influence how other, later events, occur. For instance, a reply to a received mail message is influenced by that message, and maybe by other prior messages also received. This article brings an introduction to classic causality tracking mechanisms and covers some more recent developments. The presentation is supported by a new graphical notation that allows an intuitive interpretation of the causality relations described.
Gradecast is a simple three-round algorithm presented by Feldman and Micali. The current work presents a very simple algorithm that utilized Gradecast to achieve Byzantine agreement. Two small variations of the presented algorithm lead to improved al
Many blockchain consensus protocols have been proposed recently to scale the throughput of a blockchain with available bandwidth. However, these protocols are becoming increasingly complex, making it more and more difficult to produce proofs of their
We present a model for a vacuum-like effective medium composed of the absorbing and gain media under the special designed parameters. Within the linear response theory, we prove that any pulse signal (with or without a discontinuity) through such a k
In this paper, we study local and global broadcast in the dual graph model, which describes communication in a radio network with both reliable and unreliable links. Existing work proved that efficient solutions to these problems are impossible in th
Deep neural networks (deep learning) have emerged as a technology of choice to tackle problems in natural language processing, computer vision, speech recognition and gameplay, and in just a few years has led to superhuman level performance and usher