Distributed Systems and Mobile Agents

Most of the research activity developed in last few years focused on the study of mobile and distributed systems.

Programmable Matters. In collaboration with G. A. D Luna (U. of Marseilles), P. Flocchini (Ottawa University), N. Santoro (Carleton University) and G. Viglietta (ETHZ, Zurich).

"Programmable matter" is typically viewed as a very large number of very small (possibly Nano-level) computational particles that are programmed to collectively perform some global task by means of local interactions. Such particles could have applications in a variety of important situations: smart materials, autonomous monitoring and repair, minimally invasive surgery, etc. Such computational particles are under development and there are multiple studies, mostly about their implementation issues. So one can imagine to tailor-make biological cells to operate as sensors and actuators, as programmable delivery devices, and as chemical factories for the assembly of Nano-scale structures. This vision of building cheap microscopic processing units is supported by the progress made in manufacturing micro electronic mechanical components. Yet, there is still no clear understanding which tasks can be solved by micro fabricated computing elements (both physically, and in the sense of computability) or which problems can be solved efficiently. Our main goal is to provide the algorithms to be used by those robots that we expect that soon will be cheap and small enough, as a result of the above mentioned efforts.

Sports Analytics. In collaboration with A. Tommasi and C. Zavattari.

I am also actively involved in technological transfer activities, as co-founder of a spin-off of the University of Pisa that focuses on big data analysis for sports, a field of research also known as sports analytics. Sports Data Analysis is a hot topic nowadays, and in many disciplines it’s finding its way down from the pro players into a wider range of players. In particular, the spin-off focuses on tennis: its ultimate goal is to tune an innovative way of analysing games’s data, to provide the sport practitioner, both professional and amateur, a deep understanding of his/her playing style. The approach of the studied solutions are based on cutting-edge machine learning techniques to identify those aspects of the data that better characterize a player and his/her playing style. The resulting system learns how the player likes to play at his/her peak, and adapts itself to help him/her recreate those positive feelings, rather than the “count & report” approach normally adopted in this field by other available solutions.

Control and coordination of a set of autonomous mobile robots. In collaboration with N. Santoro (Carleton University), P. Flocchini (Ottawa University), P. Widmayer e M. Cieliebak (ETH Zurigo), and V. Gervasi (Università di Pisa).

This research topic focuses on the design and analysis of algorithms to control and coordinate a set of autonomous mobile robots that are allowed to freely move on a two dimensional plane. The major goal of this work is to understand from a computational point of view the relationship between the power and the capabilities of the robots and the ability of the team to accomplish the assigned tasks. One of the outcomes of this work has been the design of a computational model to describe a distributed system populated by a set of mobile robots. The most innovative feature that distinguished the model from the previous ones present in the literature was the total asynchrony of the interactions of the robots; in fact, in previous models, the interactions between robots were modeled mostly in a synchronous way. Other results concerned the design of algorithms designed in the proposed model, that allowed the team of the robots to solve tasks that are common in robotics, such as pattern formation, gathering or homing, flocking.

Black hole search. In collaboration with N. Santoro (Crleton University), P. Flocchini (Ottawa University), and Stefan Dobrev (Ottawa University).

This research topic relates to security in networked environments where mobile agents compute. In these environments, in fact, security is the most pressing concern, and possibly the most difficult to address. The interest has been in the presence of harmful hosts, called black holes: sites that destroy any agent that might visit them without leaving any observable trace. This kind of threat exists not only on unregulated non-cooperative settings, such as Internet, but also in environments with regulated access and where agents cooperate towards common goals (e.g., sharing of resources or distribution of a computation on the Grid). In fact, a local (hardware or software) failure might render a host harmful. The focus of the research has been to design efficient strategies for the agents to locate and isolate these harmful presences, evidencing the crucial importance of addressing security issues while searching and exploring a network. Recently, the problem of addressing a wider scenario ---  the so called "dangerous networks" --- is being tackled, where security issues being dynamic and evolving over the time are studied.

Safe-Routing. In collaboration with N. Santoro (Carleton University), P. Flocchini (Ottawa University), L. Pagli (Università di Pisa), P. Widmayer (ETH Zurigo) e T. Zuwa (University of Botswana, Gaborone).

This part of the research activity has been devoted to the study of fault-tolerant routing strategies in networks. In particular, in systems using shortest-path routing tables, a single link failure is enough to interrupt the message transmission by disconnecting one or more shortest-path spanning trees. The on-line recomputation of an alternative path or of the entire new shortest path trees, rebuilding the routing tables accordingly, is usually rather expensive and causes long delays in the message’s transmission. The focus has been on the design of efficient distributed algorithms to precompute, for each link in the tree, a single non-tree link (the swap edge) able to reconnect the network should the first fail. The strategy, called point-of-failure swap rerouting is simple: normal routing information will be used to route a message to its destination. If, however, the next hop is down, the message is first rerouted towards the swap edge; once this is crossed, normal routing will resume. The work focused on distributively identifying the swap edges satisfying several optimazation criteria, such as the  distance between the point of failure and the root, or the sum of the distances of all nodes below the point of failure and the root.

Parallel Algorithms

This study is focused on the design of parallel algorithms for the Coarse-Grained Parallel Machine (CGM). In particular, we study computation geometry algorithms and algorithms on graphs. In collaboration with F. Dehne (Carleton University), and A. Pietracaprina (Università di Padova).

You can find more information on my publications page....

Conference PC and Organization

  • OPODIS 2012 (PC member)
  • OPODIS 2010 (PC member)
  • SIROCCO 2007 (co-chair)
  • FUN 2007 (PC member, Organizer and Proceedings co-editor)
  • SIROCCO 2006 (PC member)
  • OPODIS 2006 (PC member)
  • Eighth International Symposium on Stabilization, Safety, and Security of Distributed Systems -- SSS 2006 (PC member)
  • OPODIS 2005 (PC member, Organizer and Proceedings co-editor in LNCS).
  • Third International Conference on FUN WITH ALGORITHMS -- FUN 2004 (PC member)
  • EUROPAR 2004 (Distributed Systems and Algorithms topic), August 2004
  • In the Organizing Committee of the 2nd IFIP International Conference on Theoretical Computer Science (TCS@2002), August 2002, Montreal

Steering Committee


  • 2017, Progetto HOPE (Housing in Pisa for social inclusion and engagement in El- derly), nell’ambito del POR FESR 2014-2020, Obiettivo Investimenti a favore della crescita e dell’occupazione, Regione Toscana, Progetti di Innovazione Urbana (PIU)
  • 2014, Principal Investigator nel TNA project Distributed Control in Mobile Robotics Systems: Theoretical Developments and Applications, in Visionair Project (EU FP7, n. 262044), at 3DICC (STZAKI) labs, Budapest.
  • Prin (2013 – 2016), Progetti di Rilevante Interesse Nazionale (PRIN), ARS Techno- Media (Algorithms for Techno-Mediated Social Networks).
  • Prin (2010 – 2012), Progetti di Rilevante Interesse Nazionale (PRIN), The Mad Web: Models, Algorithms and Data structures for the Web and other behavioural networks.
  • co-coordinator of the EU project "MUSING: Paving The Way To The New Generation Business Intelligence"