Related papers: A Scalable Transaction Management Framework for Co…
The deployment of databases across geographically distributed regions has become increasingly critical for ensuring data reliability and scalability. Recent studies indicate that distributed databases exhibit significantly higher latency…
Existing disaggregated databases separate execution and storage layers, enabling independent and elastic scaling of resources. In most cases, this design makes transaction concurrency control (CC) a critical bottleneck, which demands…
Streaming, big data applications face challenges in creating scalable data flow pipelines, in which multiple data streams must be collected, stored, queried, and analyzed. These data sources are characterized by their volume (in terms of…
There is a growing demand for supporting inference queries that combine Structured Query Language (SQL) and Artificial Intelligence / Machine Learning (AI/ML) model inferences in database systems, to avoid data denormalization and transfer,…
Co-scheduling of jobs in data-centers is a challenging scenario, where jobs can compete for resources yielding to severe slowdowns or failed executions. Efficient job placement on environments where resources are shared requires awareness…
Beowulf clusters are very popular and deployed worldwide in support of scientific computing, because of the high computational power and performance. However, they also pose several challenges, and yet they need to provide high…
Modern applications often operate on data in multiple administrative domains. In this federated setting, participants may not fully trust each other. These distributed applications use transactions as a core mechanism for ensuring…
As securities trading systems transition to a microservices architecture, optimizing system performance presents challenges such as inefficient resource scheduling and high service response delays. Existing container orchestration platforms…
Modern cloud OLTP databases have sought performance primarily through user-space optimization - separating storage and compute layers, or distributing transactions across multiple nodes using consensus algorithms. This paper turns attention…
Many computer systems are now being redesigned to incorporate LLM-powered agents, enabling natural language input and more flexible operations. This paper focuses on handling database transactions created by large language models (LLMs).…
Sharding is a technique to speed up transaction processing in blockchains, where the $n$ processing nodes in the blockchain are divided into $s$ disjoint groups (shards) that can process transactions in parallel. We study dynamic scheduling…
Workload management for cloud databases must deal with the tasks of resource provisioning, query placement and query scheduling in a manner that meets the application's performance goals while minimizing the cost of using cloud resources.…
During the development of NoSQL-backed software, the data model evolves naturally alongside the application code. Especially in agile development, new application releases are deployed frequently causing schema changes. Eventually,…
We present HES-SQL, a novel hybrid training framework that advances Text-to-SQL generation through the integration of thinking-mode-fused supervised fine-tuning (SFT) with Group Relative Policy Optimization (GRPO). Our approach introduces…
The cloud datacenter has numerous hosts as well as application requests where resources are dynamic. The demands placed on the resource allocation are diverse. These factors could lead to load imbalances, which affect scheduling efficiency…
In safety-critical SoC applications such as automotive and aerospace, reliable transaction monitoring is crucial for maintaining system integrity. This paper introduces a drop-in Transaction Monitoring Unit (TMU) for AXI4 subordinate…
Checking whether database transactions adhere to isolation levels is a crucial yet challenging problem. We present Boomslang, the first general-purpose checking framework capable of verifying configurations that were previously uncheckable.…
Sharding is used to address the performance and scalability issues of the blockchain protocols, which divides the overall transaction processing costs among multiple clusters of nodes. Shards require less storage capacity and communication…
In RESTful APIs, interactions with a database are a common and crucial aspect. When generating whitebox tests, it is essential to consider the database's state (i.e., the data contained in the database) to achieve higher code coverage and…
Disaggregated memory (DM) separates compute and memory resources, allowing flexible scaling to achieve high resource utilization. To ensure atomic and consistent data access on DM, distributed transaction systems have been adapted, where…