Andre Cronje

The problem of peer selection, which randomly selects a peer from a set, is commonplace in Proof-of-Stake (PoS) protocols. In PoS, peers are chosen randomly with probability proportional to the amount of stake that they possess. This paper presents an approach that relates PoS peer selection to Roulette-wheel selection, which is frequently used in genetic and evolutionary algorithms or complex network modelling. In particular, we introduce the use of stochastic acceptance algorithm [6] for fast… Show more

The problem of peer selection, which randomly selects a peer from a set, is commonplace in Proof-of-Stake (PoS) protocols. In PoS, peers are chosen randomly with probability proportional to the amount of stake that they possess. This paper presents an approach that relates PoS peer selection to Roulette-wheel selection, which is frequently used in genetic and evolutionary algorithms or complex network modelling. In particular, we introduce the use of stochastic acceptance algorithm [6] for fast peer selection. The roulette-wheel selection algorithm [6] achieves O(1) complexity based on stochastic acceptance, whereas searching based algorithms may take O(N ) or O(logN ) complexity in a network of N peers. Show less

This paper introduces a new consensus protocol, so-called \emph{\stair}, for fast consensus in DAG-based trustless system. In \stair, we propose a new approach to creating local block DAG, namely \emph{x-DAG} (cross-DAG), on each node. \emph{\stair} protocol is based on our Proof-of-Stake StakeDag framework \cite{stakedag} that distinguishes participants into users and validators by their stake. Both users and validators can create and validate event blocks. Unlike StakeDag's DAG, x-DAG ensures… Show more

This paper introduces a new consensus protocol, so-called \emph{\stair}, for fast consensus in DAG-based trustless system. In \stair, we propose a new approach to creating local block DAG, namely \emph{x-DAG} (cross-DAG), on each node. \emph{\stair} protocol is based on our Proof-of-Stake StakeDag framework \cite{stakedag} that distinguishes participants into users and validators by their stake. Both users and validators can create and validate event blocks. Unlike StakeDag's DAG, x-DAG ensures that each new block has to have parent blocks from both Users and Validators to achieve more safety and liveness. Our protocol leverages a pool of validators to expose more validating power to new blocks for faster consensus in a leaderless asynchronous system. Further, our framework allows participants to join as observers / monitors, who can retrieve DAG for post-validation, but do not participate in onchain validation. Show less

Trustless systems, such as those blockchain enpowered, provide trust in the system regardless of the trust of its participants, who may be honest or malicious. Proof-of-stake (PoS) protocols and DAG-based approaches have emerged as a better alternative than the proof of work (PoW) for consensus. This paper introduces a new model, so-called \emph{\stakedag}, which aims for PoS consensus in a DAG-based trustless system. We address a general model of trustless system in which participants are… Show more

Trustless systems, such as those blockchain enpowered, provide trust in the system regardless of the trust of its participants, who may be honest or malicious. Proof-of-stake (PoS) protocols and DAG-based approaches have emerged as a better alternative than the proof of work (PoW) for consensus. This paper introduces a new model, so-called \emph{\stakedag}, which aims for PoS consensus in a DAG-based trustless system. We address a general model of trustless system in which participants are distinguished by their stake or trust: users and validators. Users are normal participants with a no assumed trust and validators are high profile participants with an established trust. We then propose a new family of stake-based consensus protocols S, operating on the DAG as in the Lachesis protocol~\cite{lachesis01}. Specifically, we propose a stake-based protocol Sϕ that leverages participants' stake as validating weights to achieve more secure distributed systems with practical Byzantine fault tolerance (pBFT) in leaderless asynchronous Directed Acyclic Graph (DAG). We then present a general model of staking for asynchronous DAG-based distributed systems. Show less

This paper presents a new framework, namely \emph{\onlay}, for scalable asynchronous distributed systems. In this framework, we propose a consensus protocol Lϕ, which is based on the Lachesis protocol~\cite{lachesis01}. At the core of Lϕ protocol, it introduces to use layering algorithm to achieve practical Byzantine fault tolerance (pBFT) in leaderless asynchronous Directed Acyclic Graph (DAG). Further, we present new online layering algorithms for the evolutionary DAGs across the nodes. Our… Show more

This paper presents a new framework, namely \emph{\onlay}, for scalable asynchronous distributed systems. In this framework, we propose a consensus protocol Lϕ, which is based on the Lachesis protocol~\cite{lachesis01}. At the core of Lϕ protocol, it introduces to use layering algorithm to achieve practical Byzantine fault tolerance (pBFT) in leaderless asynchronous Directed Acyclic Graph (DAG). Further, we present new online layering algorithms for the evolutionary DAGs across the nodes. Our new protocol achieves determistic scalable consensus in asynchronous pBFT by using assigned layers and asynchronous partially ordered sets with logical time ordering instead of blockchains. The partial ordering produced by Lϕ is flexible but consistent across the distributed system of nodes. We then present the formal model of our layering-based consensus. The model is generalized that can be applied to abstract asynchronous DAG-based distributed systems. Show less

We describe \emph{Fantom}, a framework for asynchronous distributed systems. \emph{Fantom} is based on the Lachesis Protocol~\cite{lachesis01}, which uses asynchronous event transmission for practical Byzantine fault tolerance (pBFT) to create a leaderless, scalable, asynchronous Directed Acyclic Graph (DAG).
We further optimize the \emph{Lachesis Protocol} by introducing a permission-less network for dynamic participation. Root selection cost is further optimized by the introduction of an… Show more

We describe \emph{Fantom}, a framework for asynchronous distributed systems. \emph{Fantom} is based on the Lachesis Protocol~\cite{lachesis01}, which uses asynchronous event transmission for practical Byzantine fault tolerance (pBFT) to create a leaderless, scalable, asynchronous Directed Acyclic Graph (DAG).
We further optimize the \emph{Lachesis Protocol} by introducing a permission-less network for dynamic participation. Root selection cost is further optimized by the introduction of an n-row flag table, as well as optimizing path selection by introducing domination relationships.
We propose an alternative framework for distributed ledgers, based on asynchronous partially ordered sets with logical time ordering instead of blockchains.
This paper builds upon the original proposed family of \emph{Lachesis-class} consensus protocols. We formalize our proofs into a model that can be applied to abstract asynchronous distributed system. Show less

his paper introduces a new family of consensus protocols, namely \emph{Lachesis-class} denoted by L, for distributed networks with guaranteed Byzantine fault tolerance. Each Lachesis protocol L in L has complete asynchrony, is leaderless, has no round robin, no proof-of-work, and has eventual consensus.
The core concept of our technology is the \emph{OPERA chain}, generated by the Lachesis protocol. In the most general form, each node in Lachesis has a set of k neighbours of most… Show more

his paper introduces a new family of consensus protocols, namely \emph{Lachesis-class} denoted by L, for distributed networks with guaranteed Byzantine fault tolerance. Each Lachesis protocol L in L has complete asynchrony, is leaderless, has no round robin, no proof-of-work, and has eventual consensus.
The core concept of our technology is the \emph{OPERA chain}, generated by the Lachesis protocol. In the most general form, each node in Lachesis has a set of k neighbours of most preference. When receiving transactions a node creates and shares an event block with all neighbours. Each event block is signed by the hashes of the creating node and its k peers. The OPERA chain of the event blocks is a Directed Acyclic Graph (DAG); it guarantees practical Byzantine fault tolerance (pBFT). Our framework is then presented using Lamport timestamps and concurrent common knowledge.
Further, we present an example of Lachesis consensus protocol L0 of our framework. Our L0 protocol can reach consensus upon 2/3 of all participants' agreement to an event block without any additional communication overhead. L0 protocol relies on a cost function to identify k peers and to generate the DAG-based OPERA chain. By creating a binary flag table that stores connection information and share information between blocks, Lachesis achieves consensus in fewer steps than pBFT protocol for consensus. Show less