Blockchain-based payment systems typically assume a synchronous communication network and a limited workload to confirm transactions within a bounded timeframe. These assumptions make such systems less effective in scenarios where reliable network access is not guaranteed.
Offline payment systems are designed to allow users to register offline transactions and ensure their execution once network access is restored. However, these methods often rely on specialized hardware to remain secure and tamper-proof, preventing double-spending and invalid transactions.

In this work, we introduce a novel offline payment system that does not rely on trusted hardware. Our system enables users to determine transaction fees and accept offline payments based on the trustworthiness of their peers. Users can decide whether to accept offline payments from each other based on the information our system provides.

Our system employs a smart contract to manage transactions on a blockchain for its online component. We implemented the online part of our system as an Ethereum Solidity smart contract and deployed it on the Sepolia testnet. Our performance evaluation demonstrates our system’s practicality, handling 68 Transactions Per Second (TPS) with a confirmation latency of 12 seconds on the Sepolia testnet. The system’s scalability can improve with advanced layer-1 or layer-2 blockchain solutions, enhancing throughput, decreasing latency, and reducing fees.

This paper examines the impact of faulty nodes on Practical Byzantine Fault Tolerance (PBFT) algorithms, focusing on the AWARE optimization. While AWARE improves average-case latency by assigning larger voting weights to well-connected nodes, it is vulnerable to exploitation by Byzantine nodes. We propose modifications to AWARE to enhance resilience of dynamic link latency estimation. Experiments show that comparing predicted and actual consensus latencies helps detect and mitigate performance issues caused by malicious nodes. Integrating latency information with BFT-SMaRt’s leader change algorithm offers a more robust solution. We also analyse shortcomings of AWARE dynamic leader selection system.

This paper explores the integration of weighted vot-ing mechanisms into DAG-based consensus proto-cols, such as Tusk [EuroSys’22], which promise high throughput and low latency. Weighted voting,
pioneered by protocols like WHEAT [SRDS’15] and AWARE [TDSC’20], aims to optimize perfor-mance metrics such as latency and throughput by assigning weights to nodes based on their latency with other nodes. We employ real-world latency data from CloudPing to evaluate the impact of weighted voting on Tusk, comparing them against its unweighted counterpart. Our results demon-strate significant performance improvements, with the weighted voting mechanism achieving up to 37% lower consensus latency compared to un-weighted approaches.

Streamlined Byzantine Fault Tolerant (BFT) protocols, such as HotStuff [PODC'19], and weighted voting represent two possible strategies to improve consensus in the distributed systems world. Several studies have been conducted on both techniques, but the research on combining the two is scarce. To cover this knowledge gap, we introduce a weighted voting approach on Hotstuff, along with two optimisations targeting weight assignment distribution and leader rotation in the underlying state replication protocol. Moreover, the weighted protocols developed rely on studies proving the effectiveness of a specific voting power assignment based on discrete values. We generalise this approach by presenting a novel continuous weighting scheme applied to the Hotstuff protocol to highlight the effectiveness of this technique in faulty scenarios. We prove the significant latency reduction impact of weighted voting on streamlined protocols and advocate for further research.