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cs.DB updates on arXiv.org

Block-Sphere Vector Quantization GroupAffect-4: A Multimodal Dataset of Four-Person Collaborative Interaction CogScale: Scalable Benchmark for Sequence Processing TextAlign: Preference Alignment for Text Rendering with Hierarchical Rewards LogRouter: Adaptive Two-Level LLM Routing for Log Question Answering in Big Data Systems Agentic Cost-Aware Query Planning with Knowledge Distillation for Big Data Analytics Covariance Structure and Coordinate Heterogeneity Govern Binary Quantization of Contrastive Embeddings IVF-TQ: Calibration-Free Streaming Vector Search via a Codebook-Free Residual Layer Automatic Unsupervised Ensemble Outlier Model Selection--Extended Version A Generative AI Framework for Intelligent Utility Billing CO 2 Analytics and Sustainable Resource Optimisation Towards Foundation Models for Relational Databases with Language Models and Graph Neural Networks Gaussian Relational Graph Transformer Croissant Baker: Metadata Generation for Discoverable, Governable, and Reusable ML Datasets Reducing Hallucination in Vision-Language Models via Stage-wise Preference Optimization under Distribution Shift A Horn extension of DL-Lite with NL data complexity 3D Primitives are a Spatial Language for VLMs Enabling AI-Native Mobility in 6G: A Real-World Dataset for Handover, Beam Management, and Timing Advance A CAP-like Trilemma for Large Language Models: Correctness, Non-bias, and Utility under Semantic Underdetermination EpiCastBench: Datasets and Benchmarks for Multivariate Epidemic Forecasting FERMI: Exploiting Relations for Membership Inference Against Tabular Diffusion Models Toward Multi-Database Query Reasoning for Text2Cypher Autonomous FAIR Digital Objects: From Passive Assertions to Active Knowledge HOME-KGQA: A Benchmark Dataset for Multimodal Knowledge Graph Question Answering on Household Daily Activities Detect, Localize, and Explain: Interactive Hierarchical Log Anomaly Analytics with LLM Augmentation Open Ontologies: Tool-Augmented Ontology Engineering with Stable Matching Alignment Machine Learning-Based Pre-Test Risk Stratification for PCR-Confirmed Chlamydia Using Patient-Reported Data and Urine Biomarkers Reconciling Consistency-Based Diagnosis with Actual-Causality-Based Explanations PrepBench: How Far Are We from Natural-Language-Driven Data Preparation? Anatomy of a Query: W5H Dimensions and FAR Patterns for Text-to-SQL Evaluation Building informative materials datasets beyond targeted objectives
RingBFT: Resilient Consensus over Sharded Ring Topology
Sajjad Rahnama, Suyash Gupta, Rohan Sogani, Dhruv Krishnan, Moha · 2021-07-28 · via cs.DB updates on arXiv.org

The recent surge in federated data management applications has brought forth concerns about the security of underlying data and the consistency of replicas in the presence of malicious attacks. A prominent solution in this direction is to employ a permissioned blockchain framework that is modeled around traditional Byzantine Fault-Tolerant (BFT) consensus protocols. Any federated application expects its data to be globally scattered to achieve faster access. But, prior works have shown that traditional BFT protocols are slow. This has led to the rise of sharded-replicated blockchains. Existing BFT protocols for these sharded blockchains are efficient if client transactions require access to a single-shard, but face performance degradation if there is a cross-shard transaction that requires access to multiple shards. As cross-shard transactions are common, to resolve this dilemma, we present RingBFT, a novel meta-BFT protocol for sharded blockchains. RingBFT requires shards to adhere to the ring order, and follow the principle of process, forward, and re-transmit while ensuring the communication between shards is linear. Our evaluation of RingBFT against state-of-the-art sharding BFT protocols illustrates that RingBFT achieves up to 18x higher throughput, gracefully scales to nearly 500 globally distributed nodes, and achieves a peak throughput of 1.2 million transactions per second.