BigDipper: A hyperscale BFT system with short term censorship resistance

Byzantine-fault-tolerant (BFT) protocols underlie a variety of decentralized applications including payments, auctions, data feed oracles, and decentralized social networks. In most leader-based BFT protocols, an important property that has been missing is the censorship resistance of transaction in the short term. The protocol should provide inclusion guarantees in the next block height even if the current and future leaders have the intent of censoring. In this paper, we present a BFT system, BigDipper, that achieves censorship resistance while providing fast confirmation for clients and hyperscale throughput. The core idea is to decentralize inclusion of transactions by allowing every BFT replica to create their own mini-block, and then enforcing the leader on their inclusions. To achieve this, BigDipper creates a modular system made of three components. First, we provide a transaction broadcast protocol used by clients as an interface to achieve a spectrum of probabilistic inclusion guarantees. Afterwards, a distribution of BFT replicas will receive the client's transactions and prepare mini-blocks to send to the data availability (DA) component. The DA component characterizes the censorship resistant properties of the whole system. We design three censorship resistant DA (DA-CR) protocols with distinct properties captured by three parameters and demonstrate their trade-offs. The third component interleaves the DA-CR protocols into the consensus path of leader based BFT protocols, it enforces the leader to include all the data from the DA-CR into the BFT block. We demonstrate an integration with a two-phase Hotstuff-2 BFT protocol with minimal changes. BigDipper is a modular system that can switch the consensus to other leader based BFT protocol including Tendermint

Patched Line Segment Learning for Vector Road Mapping

This paper presents a novel approach to computing vector road maps from satellite remotely sensed images, building upon a well-defined Patched Line Segment (PaLiS) representation for road graphs that holds geometric significance. Unlike prevailing methods that derive road vector representations from satellite images using binary masks or keypoints, our method employs line segments. These segments not only convey road locations but also capture their orientations, making them a robust choice for representation. More precisely, given an input image, we divide it into non-overlapping patches and predict a suitable line segment within each patch. This strategy enables us to capture spatial and structural cues from these patch-based line segments, simplifying the process of constructing the road network graph without the necessity of additional neural networks for connectivity. In our experiments, we demonstrate how an effective representation of a road graph significantly enhances the performance of vector road mapping on established benchmarks, without requiring extensive modifications to the neural network architecture. Furthermore, our method achieves state-of-the-art performance with just 6 GPU hours of training, leading to a substantial 32-fold reduction in training costs in terms of GPU hours

Modelling of a shear-type piezoelectric actuator for AFM-based vibration-assisted nanomachining

Recent research investigations have reported the benefit of enhancing conventional AFM-based nanoscale machining operations by the introduction of high frequency vibrations between the AFM tip and the processed material. The technique relies on piezoelectric actuation and is relatively straight forward to implement in practice. However, the non-linearity of piezoelectric actuators when operated under high electric field and frequency conditions can affect the dimensional accuracy of the fabricated nanostructures. To address these issues, the paper reports a method based on coupled mechanical-electrical Finite Element (FE) modelling to predict the relative motion between an AFM tip and a workpiece for vibration-assisted AFM-based nanomachining applications. In particular, the novelty of the proposed method is that it combines two classical approaches for modelling the nonlinear behaviour of piezoelectric materials. More specifically, two sources of non-linearity are considered simultaneously by combining the field-dependant model from Muller and Zhang with the frequency-dependant model from Damjanovic. The resulting combined model is employed to establish the piezoelectric constitutive equations implemented in the developed coupled field FE model. A further distinguishing characteristic of the work is that the proposed approach was subsequently validated by comparing the predicted widths of nanoscale grooves against those machined with a custom AFM-based vibration-assisted nanomachining configuration