Monitoring Distributed Component-Based Systems

TL;DR

This paper presents a novel online monitoring approach for distributed component-based systems that reconstructs global states from local traces using a lattice structure, enabling efficient property verification.

Contribution

It introduces a method to monitor distributed systems by reconstructing global states from local observations with a lattice-based approach, implemented in the RVDIST tool.

Findings

Lattice size remains stable regardless of event volume.

Monitoring overhead is low and manageable.

The approach effectively verifies properties in distributed systems.

Abstract

This paper addresses the online monitoring of distributed component-based systems with multi-party interactions against user-provided properties expressed in linear-temporal logic and referring to global states. We consider intrinsically independent components whose interactions are partitioned on distributed controllers. In this context, the problem that arises is that a global state of the system is not available to the monitor. Instead, we attach local controllers to schedulers to retrieve the concurrent local traces. Local traces are sent to a global observer which reconstructs the set of global traces that are compatible with the local ones, in a concurrency-preserving fashion. In this context, the reconstruction of the global traces is done on-the-fly using a lattice of partial states encoding the global traces compatible with the locally-observed traces. We implemented our monitoring approach in a prototype tool called RVDIST. RVDIST executes in parallel with the distributed model and takes as input the events generated from each scheduler and outputs the evaluated computation lattice. Our experiments show that, thanks to the optimisation applied in the online monitoring algorithm, i) the size of the constructed computation lattice is insensitive to the the number of received events, (ii) the lattice size is kept reasonable and (iii) the overhead of the monitoring process is cheap.

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