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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
Tracking Network Events with Write Optimized Data Structu...
Nolan Donoghue, Bridger Hahn, Helen Xu, Thomas Kroeger, David Za · 2015-11-30 · via cs.DB updates on arXiv.org

Access to network traffic records is an integral part of recognizing and addressing network security breaches. Even with the increasing sophistication of network attacks, basic network events such as connections between two IP addresses play an important role in any network defense. Given the duration of current attacks, long-term data archival is critical but typically very little of the data is ever accessed. Previous work has provided tools and identified the need to trace connections. However, traditional databases raise performance concerns as they are optimized for querying rather than ingestion. The study of write-optimized data structures (WODS) is a new and growing field that provides a novel approach to traditional storage structures (e.g., B-trees). WODS trade minor degradations in query performance for significant gains in the ability to quickly insert more data elements, typically on the order of 10 to 100 times more inserts per second. These efficient, out-of-memory data structures can play a critical role in enabling robust, long-term tracking of network events. In this paper, we present TWIAD, the Write-optimized IP Address Database. TWIAD uses a write-optimized B-tree known as a B ε tree to track all IP address connections in a network traffic stream. Our initial implementation focuses on utilizing lower cost hardware, demonstrating that basic long-term tracking can be done without advanced equipment. We tested TWIAD on a modest desktop system and showed a sustained ingestion rate of about 20,000 inserts per second.