Analysis of Parameterized Networks

In particular, the thesis will focus on parameterized networks of discrete-event systems. These are collections of interacting, isomorphic subsystems, where the number of subsystems is, for practical purposes, arbitrary; thus, the system parameter of interest is, in this case, the size of the network as characterized by the number of subsystems. Parameterized networks are reasonable models of real systems where the number of subsystems is large, unknown, or time-varying: examples include communication, computer and transportation networks. Intuition and engineering practice suggest that, in checking properties of such networks , it should be sufficient to consider a ``testbed'' network of limited size. However, there is presently little rigorous support for such an approach. In general, the problem of deciding whether a temporal property holds for a parameterized network of finite-state systems is undecidable; and the only decidable subproblems that have so far been identified place unreasonable restrictions on the means by which subsystems may interact. The key to ensuring decidability, and therefore the existence of effective solutions to the problem, is to identify restrictions that limit the computational power of the network. This can be done not only by limiting communication but also by restricting the structure of individual subsystems. In this thesis, we take both approaches, and also their combination on two different network topologies: ring networks and fully connected networks

Events in computation

SIGLEAvailable from British Library Document Supply Centre- DSC:D36018/81 / BLDSC - British Library Document Supply CentreGBUnited Kingdo

Computer Aided Verification

This open access two-volume set LNCS 13371 and 13372 constitutes the refereed proceedings of the 34rd International Conference on Computer Aided Verification, CAV 2022, which was held in Haifa, Israel, in August 2022. The 40 full papers presented together with 9 tool papers and 2 case studies were carefully reviewed and selected from 209 submissions. The papers were organized in the following topical sections: Part I: Invited papers; formal methods for probabilistic programs; formal methods for neural networks; software Verification and model checking; hyperproperties and security; formal methods for hardware, cyber-physical, and hybrid systems. Part II: Probabilistic techniques; automata and logic; deductive verification and decision procedures; machine learning; synthesis and concurrency. This is an open access book

On the Semantics of Petri Nets: Processes, Unfoldings and Infinite Computations.

PhD Thesi

Statically scheduled Process Networks

Event/Marked Graphs (EG) form a strict subset of Petri Nets. They are fundamental models in Scheduling Theory, mostly because of their absence of alternative behaviors (or conflict-freeness). It was established in the past that, under broad structural conditions, behavior of Timed Event Graphs (TEG) becomes utterly regular (technically speaking: “ultimately k-periodic”). More recently it has been proposed to use this kind of regular schedulings as syntactic types for so-called N-synchronous processes. These types remained essentially user-provided. Elsewhere there have been proposals for adding control in a “light fashion” to TEGs, not as general Petri Nets, but with the addition of Merge/Select nodes switching the data flows. This was much in the spirit of Kahn process networks [8, 9]. But usually the streams of test values governing the switches are left unspecified, which may introduce phenomena of congestion or starvation in the system, as token flow preservation becomes an issue. In the present paper we suggest to restrict the Merge/Select condition streams to (binary) k-periodic patterns as well, and to study their relations with the schedules constructed as before for TEGs, but on the extended model. We call this model Kahn-extended Event Graphs (KEG). The main result is that flow preservation is now checkable (by abstraction into another model of Weighted Marked Graphs, called SDF in the literature). There are many potential applications of KEG models, as for instance in modern Systems-on-Chip (SoC) comprising on-Chip networks. Communication links can then be shared, and the model can represent the (regular) activity schedules of the computing as well as the communicating components, after a strict scheduling has been found. They can also be used as a support to help find the solution

The Symmetry Method for Coloured Petri Nets

This booklet is the author's PhD-dissertation