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Thanh-Hai Tran

Publications and source records attributed to Thanh-Hai Tran.

5 recordsLinked to original sources

Majorum: Ebb-and-Flow Consensus with Dynamic Quorums

Dynamic availability is the ability of a consensus protocol to remain live despite honest participants going offline and later rejoining. A well-known limitation is that dynamically available protocols, on their own, cannot provide strong safety guarantees during network partitions or extended asynchrony. Ebb-and-flow protocols [SP21] address this by combining a dynamically available protocol with a partially synchronous finality protocol that irrevocably finalizes a prefix. We present Majorum, an ebb-and-flow construction whose dynamically available component builds on a quorum-based protocol (TOB-SVD). Under optimistic conditions, Majorum finalizes blocks in as few as three slots while requiring only a single voting phase per slot. In particular, when conditions remain favourable, each slot finalizes the next block extending the previously finalized one.

cs.DC↗

TOB-SVD: Total-Order Broadcast with Single-Vote Decisions in the Sleepy Model

Over the past years, distributed consensus research has expanded its focus to address challenges in large-scale, permissionless systems, such as blockchains. This shift reflects the need to accommodate dynamic participation, in contrast to the traditional model of a static set of continuously online validators. Works like Bitcoin and the sleepy model have laid the groundwork for this evolving framework. Notable contributions by Momose and Ren (CCS 2022), along with subsequent research, have introduced Total-Order Broadcast protocols that leverage Graded Agreement primitives and support dynamic participation. However, these approaches often require multiple phases of voting per decision, which can create a bottleneck for real-world, large-scale systems. To address this, our paper introduces TOB-SVD, a novel Total-Order Broadcast protocol in the sleepy model that is resilient to up to 1/2 Byzantine validators. TOB-SVD requires only a single phase of voting per decision in the best case and achieves lower expected latency compared to existing approaches offering the same optimal adversarial resilience. This work paves the way for more practical Total-Order Broadcast protocols that can be implemented in real-world systems involving a large number of validators with fluctuating participation over time.

cs.DC↗

3-Slot-Finality Protocol for Ethereum

Gasper, the consensus protocol currently employed by Ethereum, typically requires 64 to 95 slots -- the units of time during which a new chain extending the previous one by one block is proposed and voted -- to finalize. This means that under ideal conditions -- where the network is synchronous, and all chain proposers, along with more than two-thirds of the validators, behave as dictated by the protocol -- proposers construct blocks on a non-finalized chain that extends at least 64 blocks. This exposes a significant portion of the blockchain to potential reorganizations during changes in network conditions, such as periods of asynchrony. Specifically, this finalization delay heightens the network's exposure to Maximum Extractable Value (MEV) exploits, which could undermine the network's integrity. Furthermore, the extended finalization period forces users to balance the trade-off between economic security and transaction speed. To address these issues and speed up finality, we introduce a partially synchronous finality gadget, which we combine with two dynamically available consensus protocols -- synchronous protocols that ensure safety and liveness even with fluctuating validator participation levels. This integration results in secure ebb-and-flow protocols [SP 2021], achieving finality within three slots after a proposal and realizing 3-slot finality.

cs.DC↗

A case study on parametric verification of failure detectors

Partial synchrony is a model of computation in many distributed algorithms and modern blockchains. These algorithms are typically parameterized in the number of participants, and their correctness requires the existence of bounds on message delays and on the relative speed of processes after reaching Global Stabilization Time. These characteristics make partially synchronous algorithms parameterized in the number of processes, and parametric in time bounds, which render automated verification of partially synchronous algorithms challenging. In this paper, we present a case study on formal verification of both safety and liveness of the Chandra and Toueg failure detector that is based on partial synchrony. To this end, we first introduce and formalize the class of symmetric point-to-point algorithms that contains the failure detector. Second, we show that these symmetric point-to-point algorithms have a cutoff, and the cutoff results hold in three models of computation: synchrony, asynchrony, and partial synchrony. As a result, one can verify them by model checking small instances, but the verification problem stays parametric in time. Next, we specify the failure detector and the partial synchrony assumptions in three frameworks: TLA+, IVy, and counter automata. Importantly, we tune our modeling to use the strength of each method: (1) We are using counters to encode message buffers with counter automata, (2) we are using first-order relations to encode message buffers in IVy, and (3) we are using both approaches in TLA+. By running the tools for TLA+ and counter automata, we demonstrate safety for fixed time bounds. By running IVy, we prove safety for arbitrary time bounds. Moreover, we show how to verify liveness of the failure detector by reducing the verification problem to safety verification. Thus, both properties are verified by developing inductive invariants with IVy.

cs.LO↗

LG-Hand: Advancing 3D Hand Pose Estimation with Locally and Globally Kinematic Knowledge

3D hand pose estimation from RGB images suffers from the difficulty of obtaining the depth information. Therefore, a great deal of attention has been spent on estimating 3D hand pose from 2D hand joints. In this paper, we leverage the advantage of spatial-temporal Graph Convolutional Neural Networks and propose LG-Hand, a powerful method for 3D hand pose estimation. Our method incorporates both spatial and temporal dependencies into a single process. We argue that kinematic information plays an important role, contributing to the performance of 3D hand pose estimation. We thereby introduce two new objective functions, Angle and Direction loss, to take the hand structure into account. While Angle loss covers locally kinematic information, Direction loss handles globally kinematic one. Our LG-Hand achieves promising results on the First-Person Hand Action Benchmark (FPHAB) dataset. We also perform an ablation study to show the efficacy of the two proposed objective functions.

cs.CV↗