Due to the increasing popularity of P2P systems and their contribution to overall Internet traffic, it is essential to understand how content, which is the main attraction in P2P systems, is fed. The main goal of this talk is to identify and characterize those communities of users that are primarily responsible for publishing/feeding content in BitTorrent. For this purpose we have performed two large scale measurement studies that collectively identify the feeders of more than 30k torrents. Out of these measurements we conclude that a significant part of the BitTorrent’s content (40%) is fed by two different groups: (i) users concentrated min a few IP addresses of Hosting Service Providers. In particular, there is a single Hosting Provider in this community that alone is responsible of feeding 25% of the content published in the current major BitTorrent Portal. (ii) A large number of regular BitTorrent users spread across the networks of big ISPs. In addition, we characterize how the feeders of both communities behave, finding out that the typical Hosting Providers feeder (i) publishes a larger number of torrents that become more popular and (ii) seeds longer its torrents than regular users acting as feeders. Our findings suggest that a small group of users in Hosting Providers effectively leverage BitTorrent to publish content. Therefore, their presence is essential for the livelihood of BitTorrent.

In this talk I present a platform to extract models of security-relevant functionality from program binaries, enabling multiple security applications such as active botnet infiltration, finding deviations between implementations of the same functionality, vulnerability signature generation, and finding content-sniffing cross-site scripting (XSS) attacks.
In this talk, I present two applications: active botnet infiltration and finding content-sniffing XSS attacks.

His talk consists out of two parts. The first part will give an overview on the current research activities and achievements of the Distributed Multimedia Systems Research Group at the University of Oslo. This includes video streaming in MANETs and disruptive environments, publish subscribe for sparse MANETs, deviation detection with complex event processing for automated home care systems, and clean-slate Future Internet research work. The second part will focus on CacheCast, which is joint work with Lancaster University and has been initiated in the Content NoE. Due to the lack of multicast services in the Internet, applications based on single source multiple destinations transfers such as video conferencing, IP radio, IPTV must use unicast or application layer multicast. 

Nowadays it is possible to watch some TV channels in the Internet using P2P mechanisms. There are basically two ways to construct a P2P network to transmit streaming video: mesh-based and tree-based (there is also a mix of both called hybrid-based). No matter how we construct the overlay, a fundamental problem is: what is the best peer to connect with, in order to obtain the best performance? This question is even more important in the tree-based P2P networks where there is just one connection between a "parent" peer and each one of its children, so, the leaving of a parent forces all its children to reconnect to other parents. Our goal in this study is to minimize the number of orphan peers per minute, i.e. select a parent who minimizes the probability of leaving before a given peer. In order to do that, it is necessary to have other results like the distribution of the channel holding time per peer, the future lifetime of a peer given its elapsed time in a given channel and other stuff that will be described during the presentation.

La conferencia se impartirá en inglés

The current Internet includes a large number of distributed services. In order to guarantee the QoS of the communication in these services, a client has to select a close-by server with enough available resources. In order to achieve this objective, in this Thesis, we propose a simple and practical solution for Dynamic and Location Aware Server Discovery based on a Distributed Hash Table (DHT). Specifically, we decide to use a Chord DHT system (although any other DHT scheme can be used). In more detail, the solution works as follows. The servers offering a given service form a Chord-like DHT. In addition, they register their location (topological and/or geographical) information in the DHT. Each client using the service is connected to at least one server from the DHT. Eventually, a given client realizes that it is connected to a server providing a bad QoS, then, it queries the DHT in order to find an appropriate server (i.e. a close-by server with enough available resources). We define 11 design criteria, and compare our solution to the State of the Art based on them. We show that our solution is the most complete one. Furthermore, we validate the performance of our solution in two different scenarios: NAT Traversal Server Discovery and Home Agent Discovery in Mobile IP scenarios. The former serves to validate our solution in a highly dynamic environment whereas the latter demonstrates the appropriateness of our solution in more classical environments where the servers are typically hosts.

A sensor is a device capable of monitoring physical or environmental conditions, such as temperature, sound, vibration, pressure, motion or pollutants. Sensor networks composed of hundreds, or sometime of thousands of nodes, are able to gather large quantities of information enabling dynamic large scale surveillance applications to be deployed. Most of surveillance applications have a high level of criticality and can not be deployed with the current state of technology. Besides military applications that possess an obvious criticality level and have a very specific usage, surveillance applications oriented toward Critical Infrastructures and disaster relief are also very important applications that many countries have identified as critical in the near future. In this presentation, we will present the challenges in deploying mission-critical surveillance applications and will present our latest works on criticaity modeling and management.

Marco Ajmone Marsan holds a double appointment as Chief Researcher at IMDEA Networks (Spain) and Full Professor at the Department of Electronics (Dipartimento di Elettronica) of the Politecnico di Torino (Polytechnic University of Turin) (Italy). He is the founder of the Telecommunication Networks Group, one of the top research groups in networking in Europe, based at the Politecnico di Torino.

Mohamed Hefeeda is an assistant professor in the School of Computing Science, Simon Fraser University, Canada, where he leads the Network Systems Lab. He holds a Ph.D. from Purdue University, USA, and M.Sc. and B.Sc. from Mansoura University, Egypt. His research interests include multimedia networking over wired and wireless networks, peer-to-peer systems, network security, and wireless sensor networks.

Vehicular communications will increase road safety, traffic efficiency and driving comfort, by enabling vehicles to form Vehicular Ad-hoc Networks (VANETs) and to directly exchange information. Additionally, connecting the VANET to an IP based network infrastructure (e.g., the Internet) may enhance those applications, and creating the opportunity for others such as infotainment ones (e.g., games, web browsing, e-mail, etc.). One of the functionalities needed to bring IP to vehicular networks is the capability of vehicles to autoconfigure an IPv6 address. GeoSAC is a mechanism enabling IPv6 address autoconfiguration in vehicular networks based on geographic routing. In GeoSAC, as a result of the mobility of the vehicles, they cannot always use the same IP address. Each new address configuration introduces a delay during which communications are interrupted. We propose an improvement for GeoSAC, based on the caching of Router Advertisements, to avoid this disruption time. We also analytically model the probability of achieving seamless IP address reconfiguration as well as an expression for the average configuration time of nodes. The model is validated through extensive simulation. Results in different realistic scenarios show that the use of our proposed optimisation is valuable and would improve the performance in terms of configuration time and/or signaling overhead and the average configuration time expression would provide network administrators with a powerful tool that can be used during the network design.