Inferring Unobserved Events in Systems With Shared Resources and Queues

TL;DR

This paper presents a method to infer missing event data in distributed systems with shared resources by reconstructing unobserved events and their timestamps using a linear programming approach, improving process analysis accuracy.

Contribution

It introduces a multi-entity event log model and PQR-systems, enabling the inference of unrecorded events in incomplete logs through a systematic, formal approach.

Findings

Successfully reconstructed unobserved events in synthetic logs.

Validated approach on real-life baggage handling system logs.

Implemented in ProM for practical application.

Abstract

To identify the causes of performance problems or to predict process behavior, it is essential to have correct and complete event data. This is particularly important for distributed systems with shared resources, e.g., one case can block another case competing for the same machine, leading to inter-case dependencies in performance. However, due to a variety of reasons, real-life systems often record only a subset of all events taking place. To understand and analyze the behavior and performance of processes with shared resources, we aim to reconstruct bounds for timestamps of events in a case that must have happened but were not recorded by inference over events in other cases in the system. We formulate and solve the problem by systematically introducing multi-entity concepts in event logs and process models. We introduce a partial-order based model of a multi-entity event log and a corresponding compositional model for multi-entity processes. We define PQR-systems as a special class of multi-entity processes with shared resources and queues. We then study the problem of inferring from an incomplete event log unobserved events and their timestamps that are globally consistent with a PQR-system. We solve the problem by reconstructing unobserved traces of resources and queues according to the PQR-model and derive bounds for their timestamps using a linear program. While the problem is illustrated for material handling systems like baggage handling systems in airports, the approach can be applied to other settings where recording is incomplete. The ideas have been implemented in ProM and were evaluated using both synthetic and real-life event logs.