This paper introduces a novel, fast atomic-snapshot protocol for asynchronous message-passing systems. In the process of defining what "fast" means exactly, we spot a few interesting issues that arise when conventional time metrics are applied to long-lived asynchronous algorithms. We reveal some gaps in latency claims made in earlier work on snapshot algorithms, which hamper their comparative time-complexity analysis. We then come up with a new unifying time-complexity metric that captures the latency of an operation in an asynchronous, long-lived implementation. This allows us to formally grasp latency improvements of our atomic-snapshot algorithm with respect to the state-of-the-art protocols: optimal latency in fault-free runs without contention, short constant latency in fault-free runs with contention, the worst-case latency proportional to the number of active concurrent failures, and constant, close to optimal, amortized latency.

This paper introduces a novel, fast atomic-snapshot protocol for asynchronous message-passing systems. In the process of defining what "fast" means exactly, we spot a few interesting issues that arise when conventional time metrics are applied to long-lived asynchronous algorithms. We reveal some gaps in latency claims made in earlier work on snapshot algorithms, which hamper their comparative time-complexity analysis. We then come up with a new unifying time-complexity metric that captures the latency of an operation in an asynchronous, long-lived implementation. This allows us to formally grasp latency improvements of our atomic-snapshot algorithm with respect to the state-of-the-art protocols: optimal latency in fault-free runs without contention, short constant latency in fault-free runs with contention, the worst-case latency proportional to the number of active concurrent failures, and constant amortized latency.

A public ledger is a tamperproof sequence of data that can be read and augmented by everyone. Public ledgers have innumerable and compelling uses. They can secure, in plain sight, all kinds of transactions ---such as titles, sales, and payments--- in the exact order in which they occur. Public ledgers not only curb corruption, but also enable very sophisticated applications ---such as cryptocurrencies and smart contracts. They stand to revolutionize the way a democratic society operates. As currently implemented, however, they scale poorly and cannot achieve their potential. Algorand is a truly democratic and efficient way to implement a public ledger. Unlike prior implementations based on proof of work, it requires a negligible amount of computation, and generates a transaction history that will not "fork" with overwhelmingly high probability. Algorand is based on (a novel and super fast) message-passing Byzantine agreement. For concreteness, we shall describe Algorand only as a money platform.

The last decade has seen a variety of Asset-Transfer systems designed for decentralized environments. The major problem these systems address is double-spending, and solving it inherently imposes strong trust assumptions on the system participants. In this paper, we take a non-orthodox approach to the double-spending problem that might suit better realistic environments in which these systems are to be deployed. We consider the decentralized trust setting, where each user may independently choose who to trust by forming their local quorums. In this setting, we define k-Spending Asset Transfer, a relaxed version of asset transfer which bounds the number of times a system participant may spend an asset it received. We establish a precise relationship between the decentralized trust assumptions and k, the optimal spending number of the system.

The last decade has seen a variety of Asset-Transfer systems designed for decentralized environments. To address the problem of double-spending, these systems inherently make strong model assumptions and spend a lot of resources. In this paper, we take a non-orthodox approach to the double-spending problem that might suit better realistic environments in which these systems are to be deployed. We consider the decentralized trust setting, where each user may independently choose who to trust by forming its local quorums. In this setting, we define k-Spending Asset Transfer, a relaxed version of asset transfer which bounds the number of times the same asset can be spent. We establish a precise relationship between the decentralized trust assumptions and k, the optimal spending number of the system.