Ore 08.30-08.45: Presentazione Miniscuola (Prof. Domenico Rosaci)

Ore 08.45-09.45: Prof. Giuseppe M.L. Sarnè: Social Trust: Foundations and Perspectives.

Abstract: Social networks connect people providing them with a versatile Web environment exploitable both to share information and experiences with like-minded people and for accessing to services. In such a context, social networks found their success on the level of mutual trust existing among their members. Given its relevance and the overwhelming studies investigated on the social trust, this talk searches to provide a reasoned approach to the matter.

Giuseppe M. L. Sarnè is assistant professor of Computer Science at the University Mediterranea of Reggio Calabria, Italy. His research interests include distributed artificial intelligence, multi-agent systems, trust and reputation in social communities. He has published more than 110 papers in outstanding international journals and conference proceedings. He is Associate Editor of the international journal Electronic Commerce Research and Application, reviewer of a number of international journals and conferences and member of a number of conference PCs.

Ore 09.45-10.45: Prof. Pasquale De Meo: Quickly finding communities in large networks by means of edge centralities.

Abstract: A community within a network is a group of vertices densely connected to each other but less connected to the vertices outside. The problem of detecting communities has attracted the interest of researchers from many scientific areas like Computer Science, Biology and Sociology. Most of the existing algorithms to find communities count on the topological features of the network and often do not scale well on large, real-life instances. We propose a strategy to enhance existing community detection algorithms by adding a pre-processing step in which edges are weighted according to their centrality w.r.t. the network topology. The centrality of an edge reflects its contribute to making arbitrary graph traversals as quick as possible. We adopted a Monte Carlo strategy to compute edge centralities and we prove that the proposed method scales well also on large-scale networks. We used our approach in combination with three state-of-the-art community detection algorithms, namely the Louvain method, COPRA and OSLOM. Experimental results show that our method raises the accuracy of existing algorithms both on synthetic and real-life datasets.

Pasquale De Meo is an associate professor of computer science at the Department of Ancient and Modern Civilizations at the University of Messina, Italy. His main research interests are in the area of social networks, recommender systems, and user profiling. De Meo has a PhD in systems engineering and computer science from the University of Calabria. His PhD thesis was selected as the Best Italian PhD thesis in Artificial Intelligence by the AI*IA (Italian Association for Artificial Intelligence). He has been the Marie Curie Fellow at Vrije Universiteit Amsterdam. He has extensively published on top Computer Science Journals like Communications of the ACM, IEEE Transactions on Knowledge and Data Engineering, ACM Transactions on Internet Technology, ACM Transactions on Intelligent Systems, IEEE Transactions on Systems, Man and Cybernetics, Information Systems.

Ore 10.45-11.00: Coffee break

Ore 11.00-12.00: Ing. Fabrizio Messina: A trust-aware, self-organizing system for large-scale federations of utility computing infrastructures.

Abstract: On-demand distributed computing environments, like Cloud federations, consist of nodes that individually manage local resources intended to be served to clients. A client, of a broker, needing some resources, it has the problem of finding the most suitable nodes capable of providing them. In addition, a provider node may be in need to efficiently locate resources for itself, given the emerging, highly competitive, context of large-scale federations. A node may decide to publish a set of resources/ services wider than the one it has currently available, should such a node be assigned a job for which its actual resources are insufficient, it could end up requiring the collaboration of other nodes. Hence the crucial problem, for nodes and clients alike, is to determine the most promising collaborators. For this purpose, in the competitive and demanding scenarios considered, we advocate taking into account the trustworthiness of nodes in declaring their capabilities, i.e., to help it making an effective selection of possible collaborators, each node should be provided with a trust model for accurately evaluating the trustworthiness of its interlocutors. The talk will come to explain the design of a trust-based approach for large-scale federations of Utility Computing infrastructures, which allows any node to find the most suitable collaborators in an efficient way, avoiding exploration of the whole node space. The solution is based on a fully decentralized approach that allows nodes of a federation to be organized in an overlay network having a ``social structure'' (e.g. a small world) which is built on the basis of some criteria.

This enables any customer or provider in need of collaborators to determine a suitable set of candidate nodes within which to search in an efficient way.

Fabrizio Messina received his PhD in Computer Science from the Department of Mathematics and Informatics of the University of Catania, Italy in 2009. He is currently research fellow in the same department. He is author of more than 60 papers in international conferences and journals. He currently serves as Managing Editor of the International Journal of Grid and Utility Computing. His research interests includes cloud and grid computing, trust and recommender systems, complex systems, simulation systems.

Ore 12.00-13.00: Tavola Rotonda: The role of Trust for Social Agents. Coordina il Prof. Corrado Santoro.