Research Papers

This work presents a mechanism for dynamically adapting a decentralized network to fluctuations in transaction flow, based on a directed acyclic graph (DAG) ledger structure. By incorporating this approach, a system can effectively respond to changing network workloads, ensuring a self-sufficient and adaptive environment for processing a transaction throughout its entire lifespan. Although this dynamic adoption mechanism is designed explicitly for the current version of the Waterfall platform, the presented approach possesses the potential to be applied across a wide range of networks built on the blockDAG principle, owing to a set of tuning parameters.

A consensus protocol is a crucial mechanism of distributed networks by which nodes can coordinate their actions and the current state of data. This article describes a BlockDAG consensus algorithm based on the Proof of Stake approach. The protocol provides network participants with cross-voting for the order of blocks, which, in the case of a fair vote, guarantees a quick consensus. Under conditions of dishonest behavior, cross-voting ensures that violations will be quickly detected. In addition, the protocol assumes the existence of a Coordinating network containing information about the approved ordering, which qualitatively increases security and also serves to improve network synchronization.

Decentralized public platforms are becoming increasingly popular due to a growing number of applications for various areas of business, finance, and social life. Authorless nodes can easily join such networks without any confirmation, making a transparent system of rewards and punishments crucial for the self-sustainability of public platforms. To achieve this, a system for incentivizing and punishing Workers’ behavior should be tightly integrated into the corresponding consensus protocol, taking into account all of its features, and facilitating a favorable and supportive environment with equal rights for all participants. All honest nodes make common decisions based only on information recorded into the ledger without overloading the network with additional interactions, since such data are always identical and available. The main goal of this work is to design a fair distribution of rewards among honest Workers, and to establish values for penalties for faulty ones, to ensure the general economic equilibrium of the Waterfall platform.

In the article, we study the horizontal scaling of the Waterfall or similar blockDAG networks by partitioning them into subnetworks by applying hierarchical and graph-based clustering algorithms. It leads to the reducing the network load and, in addition, to the increasing of the potential performance parameters of the underlying protocol. We consider methods of topology construction, propose clustering algorithms, and perform a simulation of a network partitioning into subnetworks.

This article explains the fundamental principles of the economic policy that are integrated into the decentralized public platform Waterfall. The platform has a DAG (Directed Acyclic Graph) based system architecture and is designed to develop decentralized applications and financial services. The main goal of this work is to create a favorable environment that incentivizes positive behavior from each network participant and from the system as a whole. Economic leverages ensure general equilibrium to provide an optimal data replication ratio, attack protection, and affordable transaction fees. Although this model of tokenomic is designed explicitly for the current version of the Waterfall platform named Salto Collazo, the presented approaches possess the potential to be applied across a broad spectrum of decentralized public platforms, owing to their inherent transparency and a set of tuned parameters.

This article explains the fundamental principles of the economic policy that are integrated into the decentralized public platform Waterfall. The platform has a DAG (Directed Acyclic Graph) based system architecture and is designed to develop decentralized applications and financial services. The main goal of this work is to create a favorable environment that incentivizes positive behavior from each network participant and from the system as a whole. Economic leverages ensure general equilibrium to provide an optimal data replication ratio, attack protection, and affordable transaction fees. Although this model of tokenomic is designed explicitly for the current version of the Waterfall platform named Salto Collazo, the presented approaches possess the potential to be applied across a broad spectrum of decentralized public platforms, owing to their inherent transparency and a set of tuned parameters.

Decentralized platforms like blockchain have been attracting significant attention in recent years, especially in the context of financial and payment systems. They are designed to provide a transparent, secure, and reliable environment for digital transactions without the need for a central authority. The core of a decentralized platform like blockchain is a consensus layer that allows all participants (called Workers), who properly operate and follow all network protocols and have access to the same state of the distributed ledger, to coordinate their actions and arrive at the same decisions. However, some Workers may be temporarily offline at their own discretion, without any confirmation, or their work may be faulty due to technical circumstances, resulting in unpredictable behavior. The goal of this article is to present an approach for multi-objective optimizing of Byzantine fault tolerance (BFT)-based consensus protocols, to reduce the impact on the network of faulty participants. Two criteria were considered – minimization of the number of sent service messages, and maximization of the mathematical expectation of the number of produced blocks. The result is a method to determine the optimal committee size and distribution of Workers, depending on their total number in the network and the expected proportion of Byzantine faulty nodes. All protocol amendments presented in this work are tested with corresponding simulation models and have demonstrated notable enhancements in the performance of the system and decreased the load on network nodes. These improvements will be implemented to the consensus protocol Gozalandia on the Waterfall platform, enhancing its overall reliability, performance, and security. In addition, the presented optimizing algorithm can be applied to a wide range of consensus protocols in blockchains, where blocks must be signed by randomly selected committees to confirm their validity.