Real-time Stream-based Monitoring

TL;DR

RTLola is a novel stream-based language for real-time system monitoring that efficiently handles sliding windows and aggregation, providing memory guarantees and practical applicability for reactive systems.

Contribution

The paper introduces RTLola, a new language integrating sliding windows with aggregation for real-time properties, along with an efficient evaluation algorithm and memory analysis methods.

Findings

Efficient evaluation algorithm for sliding windows using interval partitioning.

Memory guarantees based on fixed monitor output rate.

Practical applicability demonstrated through real-world examples.

Abstract

We introduce RTLola, a new stream-based specification language for the description of real-time properties of reactive systems. The key feature is the integration of sliding windows over real-time intervals with aggregation functions into the language. Using sliding windows we can detach fixed-rate output streams from the varying rate input streams. We provide an efficient evaluation algorithm of the sliding windows by partitioning the windows into intervals according to a given monitor frequency. For useful aggregation functions, the intervals allow a more efficient way to compute the aggregation value by dynamically reusing interval summaries. In general, the number of input values within a single window instance can grow arbitrarily large disallowing any guarantees on the expected memory consumption. Assuming a fixed monitor output rate, we can provide memory guarantees which can be computed a-priori. Additionally, for specifications using certain classes of aggregation functions, we can perform a more precise, better memory analysis. We demonstrate the applicability of the new language on practical examples.