Moreno Marzolla’s research while affiliated with University of Bologna and other places

In this paper we describe a heuristic for decomposing a directed graph into factors according to the direct product (also known as Kronecker, cardinal or tensor product). Given a directed, unweighted graph G with adjacency matrix $\mathbf{Adj}(G)$, our heuristic aims at identifying two graphs $G_1$ and $G_2$ such that $G = G_1 \times G_2$, where $G_1 \times G_2$ is the direct product of $G_1$ and $G_2$. For undirected, connected graphs it has been shown that graph decomposition is "at least as difficult" as graph isomorphism; therefore, polynomial-time algorithms for decomposing a general directed graph into factors are unlikely to exist. Although graph factorization is a problem that has been extensively investigated, the heuristic proposed in this paper represents - to the best of our knowledge - the first computational approach for general directed, unweighted graphs. We have implemented our algorithm using the MATLAB environment; we report on a set of experiments that show that the proposed heuristic solves reasonably-sized instances in a few seconds on general-purpose hardware. Although the proposed heuristic is not guaranteed to find a factorization, even if one exists; however, it always succeeds on all the randomly-generated instances used in the experimental evaluation.

We present a solution for accountability in Cloud infrastructures based on blockchain ^a . We show that, through smart contracts, it is possible to create an unforgeable log that can be used for auditing and automatic Service Level Agreement (SLA) verification. As a practical case study, we consider Cloud storage services and define interaction protocols for registering the outcome of each file operation in the blockchain. We developed a prototype implementation that runs on the GoQuorum, Hyperledger Besu, and Polygon blockchains, using different consensus protocols. Using a dedicated testbed, we discuss the performance of our implementation in terms of latencies, error rates and gas usage. Results demonstrate the viability of our approach over permissioned blockchains, with better performance for the Polygon and GoQuorum Raft decentralized systems. Our implementation enables interoperability, given that it is supported by the Ethereum Virtual Machine which currently is underlying several blockchain platforms.

Queueing networks and Markov chains are widely used for conducting performance and reliability studies. In this paper we describe the queueing package, a free software package for queueing networks and Markov chain analysis for GNU Octave. The queueing package provides implementations of numerical algorithms for computing transient and steady-state performance measures of discrete and continuous Markov chains, and for steady-state analysis of single-station queueing systems and queueing networks. We illustrate the design principles of the queueing package, describe its most salient features and provide some usage examples.

Queueing networks and Markov chains are a widely used modeling notation that has been successfully applied to many kind of systems. In this paper we describe the queueing package, a free software package for product-form queueing networks and Markov chains analysis written in GNU Octave. The queueing package allows users to compute performance measures of Markov chains, single-station queueing systems and product- and some non product-form Queueing Network (QN) models. We present some practical examples showing how the queueing package can be used for reliability analysis, capacity planning and general systems modeling.

In this paper we describe a heuristic for decomposing a directed graph into factors according to the direct product (also known as Kronecker, cardinal or tensor product). Given a directed, unweighted graph~G with adjacency matrix Adj(G), our heuristic searches for a pair of graphs~$G_1$ and~$G_2$ such that $G = G_1 \otimes G_2$, where $G_1 \otimes G_2$ is the direct product of~$G_1$ and~$G_2$. For undirected, connected graphs it has been shown that graph decomposition is "at least as difficult" as graph isomorphism; therefore, polynomial-time algorithms for decomposing a general directed graph into factors are unlikely to exist. Although graph factorization is a problem that has been extensively investigated, the heuristic proposed in this paper represents -- to the best of our knowledge -- the first computational approach for general directed, unweighted graphs. We have implemented our algorithm using the MATLAB environment; we report on a set of experiments that show that the proposed heuristic solves reasonably-sized instances in a few seconds on general-purpose hardware.