Publications

Here's a list of my publications, ordered by year.

A useful link is my profile on Google Scholar:

Icons description: J="Journal article", C="in Conference proceedings", B="Book chapter". All the publications listed here have been peer-reviewed.

Last update: 2021-07-26.

  • J

    2021

    Multi-Objective Optimization of Deadline and Budget-Aware Workflow Scheduling in Uncertain Clouds

    M. C. Calzarossa, M. L. Della Vedova, L. Massari, G. Nebbione, D. Tessera

    IEEE Access, 9:89891–89905, June 2021.

    doi:10.1109/ACCESS.2021.3091310

    Cloud technologies are being used nowadays to cope with the increased computing and storage requirements of services and applications. Nevertheless, decisions about resources to be provisioned and the corresponding scheduling plans are far from being easily made especially because of the variability and uncertainty affecting workload demands as well as technological infrastructure performance. In this paper we address these issues by formulating a multi-objective constrained optimization problem aimed at identifying the optimal scheduling plans for scientific workflows to be deployed in uncertain cloud environments. In particular, we focus on minimizing the expected workflow execution time and monetary cost under probabilistic constraints on deadline and budget. According to the proposed approach, this problem is solved offline, that is, prior to workflow execution, with the intention of allowing cloud users to choose the plan of the Pareto optimal set satisfying their requirements and preferences. The analysis of the combined effects of cloud uncertainty and probabilistic constraints has shown that the solutions of the optimization problem are strongly affected by uncertainty. Hence, to properly provision cloud resources, it is compelling to precisely quantify uncertainty and take explicitly into account its effects in the decision process.
  • J

    2021

    Algoritmo

    M. L. Della Vedova

    Dizionario di dottrina sociale della Chiesa, pages 170–175, March 2021.

    doi:10.26350/dizdott_000020

    Un algoritmo è la descrizione di una procedura per risolvere un problema attraverso una sequenza finita di passi elementari. Di particolare interesse sono gli algoritmi “computazionali” perché possono essere eseguiti da un computer. Si può affermare che tutto (e solo) quello che un computer fa è eseguire algoritmi.
  • C

    2019

    Modeling and predicting dynamics of heterogeneous workloads for cloud environments

    M. C. Calzarossa, M. L. Della Vedova, L. Massari, G. Nebbione, D. Tessera

    In 2019 IEEE Symposium on Computers and Communications (ISCC), 1–7. Barcelona, Spain, June 2019. IEEE.

    doi:10.1109/ISCC47284.2019.8969761

  • J

    2019

    A methodological framework for cloud resource provisioning and scheduling of data parallel applications under uncertainty

    M. C. Calzarossa, M. L. Della Vedova, D. Tessera

    Future Generation Computer Systems, 93:212–223, April 2019.

    doi:10.1016/j.future.2018.10.037

  • C

    2019

    Tuning Genetic Algorithms for Resource Provisioning and Scheduling in Uncertain Cloud Environments: Challenges and Findings

    M. C. Calzarossa, L. Massari, G. Nebbione, M. L. Della Vedova, D. Tessera

    In 2019 27th Euromicro International Conference on Parallel, Distributed and Network-Based Processing (PDP), 174–180. Pavia, Italy, February 2019. IEEE.

    doi:10.1109/EMPDP.2019.8671564

  • B

    2019

    A Methodological Approach for Time Series Analysis and Forecasting of Web Dynamics

    M. C. Calzarossa, M. L. Della Vedova, L. Massari, G. Nebbione, D. Tessera

    In N. T. Nguyen, R. Kowalczyk, F. Xhafa, editors, Transactions on Computational Collective Intelligence XXXIII, volume 11610 of Lecture Notes in Computer Science, pages 128–143.Springer Berlin Heidelberg, Berlin, Heidelberg, 2019.

    doi:10.1007/978-3-662-59540-4_7

  • J

    2018

    Learning Markov Equivalence Classes of Directed Acyclic Graphs: An Objective Bayes Approach

    F. Castelletti, G. Consonni, M. L. Della Vedova, S. Peluso

    Bayesian Analysis, December 2018.

    doi:10.1214/18-BA1101

  • C

    2018

    Automatic Online Fake News Detection Combining Content and Social Signals

    M. L. Della Vedova, E. Tacchini, S. Moret, G. Ballarin, M. DiPierro, L. de Alfaro

    In 2018 22nd Conference of Open Innovations Association (FRUCT), 272–279. Jyvaskyla, May 2018. IEEE.

    doi:10.23919/FRUCT.2018.8468301

  • J

    2017

    Adaptive Real-Time Scheduling of Cyber-Physical Energy Systems

    D. De Martini, G. Benetti, M. L. Della Vedova, T. Facchinetti

    ACM Transactions on Cyber-Physical Systems, 1(4):1–25, October 2017.

    doi:10.1145/3047412

    This article addresses the application of real-time scheduling to the reduction of the peak load of power consumption generated by electric loads in Cyber-Physical Energy Systems (CPES). The goal is to reduce the peak load while achieving a desired Quality of Service of the physical system under control. The considered physical processes are characterized by integrator dynamics and modelled as sporadic real-time activities. Timing constraints are obtained from physical parameters and are used to manage the activation of electric loads by a real-time scheduling algorithm. As a main contribution, an algorithm derived from the multi-processor real-time scheduling domain is proposed to efficiently deal with a high number of physical processes (i.e., electric loads), making its scalability suitable for large CPES, such as smart energy grids. The cyber-physical nature of the proposed method arises from the tight interaction between the physical processes operated by the electric loads, and the applied scheduling. To allow the use of the proposed approach in practical applications, modelling approximations and uncertainties on physical parameters are explicitly included in the model. An adaptive control strategy is proposed to guarantee the requirements on physical values under control in presence of modelling and measurement uncertainties. The compensation for such uncertainties is done by dynamically adapting the values of timing parameters used by the scheduler. Formal results have been derived to put into relationship the values of quantities describing the physical process with real-time parameters used to model and to schedule the activation of loads. The performance of the method is evaluated by means of physically accurate simulations of thermal systems, showing a remarkable reduction of the peak load and a robust enforcement of the desired physical requirements.
  • C

    2017

    Peak load optimization through 2-dimensional packing and multi-processor real-time scheduling

    D. De Martini, G. Benetti, F. Cipolla, D. Caprino, M. L. Della Vedova, T. Facchinetti

    In Proceedings of the Computing Frontiers Conference, 275–278. Siena Italy, May 2017. ACM.

    doi:10.1145/3075564.3075587

  • C

    2017

    Some like it Hoax: Automated fake news detection in social networks

    E. Tacchini, G. Ballarin, M. L. Della Vedova, S. Moret, L. de Alfaro

    In CEUR Workshop Proceedings, volume 1960. Skopje, 2017.

    URL: http://ceur-ws.org/Vol-1960/paper2.pdf

    In the recent years, the reliability of information on the Internet has emerged as a crucial issue of modern society. Social network sites (SNSs) have revolutionized the way in which information is spread by allowing users to freely share content. As a consequence, SNSs are also increasingly used as vectors for the diffusion of misinformation and hoaxes. The amount of disseminated information and the rapidity of its diffusion make it practically impossible to assess reliability in a timely manner, highlighting the need for automatic online hoax detection systems. As a contribution towards this objective, we show that Facebook posts can be classified with high accuracy as hoaxes or non-hoaxes on the basis of the users who “liked” them. We present two classification techniques, one based on logistic regression, the other on a novel adaptation of boolean crowdsourcing algorithms. On a dataset consisting of 15,500 Facebook posts and 909,236 users, we obtain classification accuracies exceeding 99\% even when the training set contains less than 1\% of the posts. We further show that our techniques are robust: they work even when we restrict our attention to the users who like both hoax and non-hoax posts. These results suggest that mapping the diffusion pattern of information can be a useful component of automatic hoax detection systems.
  • J

    2016

    The Economics of Cloud Parallelism under Uncertainty

    M. L. Della Vedova, D. Tessera, M. C. Calzarossa, J. Weinman

    IEEE Cloud Computing, 3(6):16–22, November 2016.

    doi:10.1109/MCC.2016.137

  • C

    2016

    Probabilistic provisioning and scheduling in uncertain Cloud environments

    M. L. Della Vedova, D. Tessera, M. C. Calzarossa

    In 2016 IEEE Symposium on Computers and Communication (ISCC), 797–803. Messina, June 2016. IEEE.

    doi:10.1109/ISCC.2016.7543834

  • J

    2016

    Electric load management approaches for peak load reduction: A systematic literature review and state of the art

    G. Benetti, D. Caprino, M. L. Della Vedova, T. Facchinetti

    Sustainable Cities and Society, 20:124–141, January 2016.

    doi:10.1016/j.scs.2015.05.002

  • B

    2016

    Workloads in the Clouds

    M. C. Calzarossa, M. L. Della Vedova, L. Massari, D. Petcu, M. I. M. Tabash, D. Tessera

    In L. Fiondella, A. Puliafito, editors, Principles of Performance and Reliability Modeling and Evaluation, Springer Series in Reliability Engineering, pages 525–550.Springer International Publishing, Cham, 2016.

    doi:10.1007/978-3-319-30599-8_20

  • C

    2015

    Applying limited-preemptive scheduling to peak load reduction in smart buildings

    D. Caprino, M. L. Della Vedova, T. Facchinetti

    In 2015 IEEE 20th Conference on Emerging Technologies & Factory Automation (ETFA), 1–8. Luxembourg, Luxembourg, September 2015. IEEE.

    doi:10.1109/ETFA.2015.7301454

  • J

    2014

    Peak shaving through real-time scheduling of household appliances

    D. Caprino, M. L. Della Vedova, T. Facchinetti

    Energy and Buildings, 75:133–148, June 2014.

    doi:10.1016/j.enbuild.2014.02.013

  • C

    2014

    Modeling and real-time control of an industrial air multi-compressor system

    T. Facchinetti, G. Benetti, M. L. Della Vedova

    In Proceedings of the 9th IEEE International Symposium on Industrial Embedded Systems (SIES 2014), 67–76. Pisa, June 2014. IEEE.

    doi:10.1109/SIES.2014.6871189

  • C

    2013

    Real-Time Scheduling for Peak Load Reduction in a Large Set of HVAC Loads

    M. L. Della Vedova, T. Facchinetti

    In ENERGY 2013, The Third International Conference on Smart Grids, Green Communications and IT Energy-aware Technologies, 161–166. Lisbon, Portugal, March 2013. IARIA.

    URL: https://goo.gl/JH3ooQ

    This paper presents a technique to predictably coordinate the activation of Heating, Ventilation and Air Conditioning systems (HVACs) in order to limit the overall peak load of power consumption (peak shaving). The proposed solution represents a viable approach to the Demand-Side Management in the context of a smart grid for this type of loads. The coordination method performs a load shifting based on the discipline of real-time scheduling traditionally studied in the field of computing systems. With this approach, individual constraints on the temperature associated with the activation of each HVAC can be satisfied. The main advantage of the proposed technique is its low computational complexity, which allows to manage large sets of loads. A specific approach is proposed and evaluated to deal with large sets of loads by properly partitioning the load set into sub-sets (scheduling groups) that are scheduled independently from each other. Simulation results based on realistic parameters show that the peak load can be reduced by 35\% in normal working conditions, and up to 60\% with respect to worst case situations, without affecting the comfort achieved by each HVAC.
  • C

    2012

    Feedback scheduling of real-time physical systems with integrator dynamics

    M. L. Della Vedova, T. Facchinetti

    In Proceedings of 2012 IEEE 17th International Conference on Emerging Technologies & Factory Automation (ETFA 2012), 1–8. Krakow, Poland, September 2012. IEEE.

    doi:10.1109/ETFA.2012.6489581

  • C

    2012

    Real-time scheduling for industrial load management

    M. L. Della Vedova, T. Facchinetti

    In 2012 IEEE International Energy Conference and Exhibition (ENERGYCON), 707–713. Florence, Italy, September 2012. IEEE.

    doi:10.1109/EnergyCon.2012.6348243

  • C

    2012

    Platooning control of autonomous nonholonomic mobile robots in a human-robot coexisting environment

    M. L. Della Vedova, M. Rubagotti, T. Facchinetti, A. Ferrara

    In 2012 American Control Conference (ACC), 6569–6574. Montreal, QC, June 2012. IEEE.

    doi:10.1109/ACC.2012.6314938

  • J

    2011

    Time-optimal sliding-mode control of a mobile robot in a dynamic environment

    M. Rubagotti, A. Ferrara, M. L. Della Vedova

    IET Control Theory & Applications, 5(16):1916–1924, November 2011.

    doi:10.1049/iet-cta.2010.0678

  • J

    2011

    Real-Time Modeling for Direct Load Control in Cyber-Physical Power Systems

    T. Facchinetti, M. L. Della Vedova

    IEEE Transactions on Industrial Informatics, 7(4):689–698, November 2011.

    doi:10.1109/TII.2011.2166787

  • C

    2011

    Electric loads as Real-Time tasks: An application of Real-Time Physical Systems

    M. L. Della Vedova, E. Di Palma, T. Facchinetti

    In 2011 7th International Wireless Communications and Mobile Computing Conference, 1117–1123. Istanbul, Turkey, July 2011. IEEE.

    doi:10.1109/IWCMC.2011.5982697

  • C

    2011

    Right Sizing Customer Care: An Approach for Sustainable Service Level Agreements

    T. Barroero, G. Motta, M. L. Della Vedova

    In 2011 International Joint Conference on Service Sciences, 40–43. Taipei, May 2011. IEEE.

    doi:10.1109/IJCSS.2011.16

  • C

    2010

    On real-time physical systems

    M. L. Della Vedova, M. Ruggeri, T. Facchinetti

    In Proceedings of the 18th International Conference on Real-Time and Network Systems (RTNS), 41–49. Toulouse, France, November 2010.

    URL: https://hal.inria.fr/RTNS2010/hal-00544477

  • C

    2010

    Real-Time Modeling and Control of a Cyber-Physical Energy System

    T. Facchinetti, M. L. Della Vedova

    In Energy Aware Design and Analysis of Cyber Physical Systems (WEA-CPS), 2010 First International Workshop on. April 2010.

  • C

    2009

    Real-time platooning of mobile robots: design and implementation

    M. L. Della Vedova, T. Facchinetti, A. Ferrara, A. Martinelli

    In 2009 IEEE Conference on Emerging Technologies & Factory Automation, 1–4. Palma de Mallorca, Spain, September 2009. IEEE.

    doi:10.1109/ETFA.2009.5347246

  • C

    2009

    Visual Interaction for Real-Time Navigation of Autonomous Mobile Robots

    M. L. Della Vedova, T. Facchinetti, A. Ferrara, A. Martinelli

    In 2009 International Conference on CyberWorlds, 211–218. Bradford, September 2009. IEEE.

    doi:10.1109/CW.2009.24