MIDDLEWARE

Machine Learning (ML) is more than just training models, the whole life-cycle must be considered. Once deployed, a ML model needs to be constantly managed, supervised and debugged to guarantee its availability, validity and robustness in dynamic ...

Zero-knowledge proofs (ZKPs) have garnered much attention recently. They have witnessed applicability in anonymizing tokens (e.g., Tornado Cash) and increasing transaction throughput (e.g., ZK-Rollups) for blockchains backing cryptocurrencies. ZKPs are ...

Network faults are often transient and hence hard to detect and difficult to resolve. Our study conducts an analysis of Kafka's network fault tolerance capabilities, one of the widely used distributed stream processing system (DSPS). Across different ...

Cloud applications are often implemented as distributed services that call each other, creating complex application call graphs. Tracking such call graphs is crucial to diagnose and resolve performance issues. This paper presents DyMonD, a holistic ...

Serverless functions provide high levels of parallelism, short startup times, and "pay-as-you-go" billing. These attributes make them a natural substrate for data analytics workflows. However, the impossibility of direct communication between functions ...

Database Management Systems (DBMS) operated on cloud resources are the storage backend for a multitude of data-intensive applications. In the process of finding the optimal cloud and DBMS, benchmarking is the common approach to evaluate the non-...

We present Bricks, a configurable coordination service that provides a set of features as building blocks. The developers then select and integrate those building blocks into components for their distributed applications. For example, multiple ...

This paper presents GNOSIS, an event processing engine to detect complex event patterns over multimodal data streams. GNOSIS follows a query-driven approach where users can write complex event queries using Multimodal Event Processing Language (MEPL). ...