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.

The conference will be conducted in English

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.

Wireless ad hoc networks have emerged to be used in scenarios where it is required or desired to have wireless communications among a variety of devices without relying on any infrastructure or central management.

One of the fundamental operations in wireless ad hoc networks is broadcasting, where a wireless device (simply called a node) disseminates a message to all other nodes in the network. A major challenge of efficient broadcast algorithms is to reduce the number of transmissions required to disseminate a message. Unfortunately, minimizing the total number of required transmissions is an NP-hard problem even when the whole network topology is known by every node. Reducing the number of transmissions becomes more challenging in local broadcast algorithms, where each node makes decision (whether or not to transmit a received message) based on local neighborhood information. The common belief is that local broadcast algorithms are not able to guarantee both full delivery and a good bound on the number of transmissions.

Delay Tolerant Networks (DTN) are networks of self-organizing wireless nodes, where end-to-end connectivity is intermittent. In these networks, content or information between nodes is exchanged (opportunistically), whenever two nodes are within range ("in contact"). Forwarding decisions are generally probabilistic and based on locally collected knowledge about node behavior (e.g., past contacts between nodes) to predict future contact opportunities. The use of complex network analysis has been recently suggested to perform this prediction task and improve the performance of opportunistic (DTN) routing. Contacts seen in the past are aggregated to a "Social Graph", and a variety of metrics (e.g., entrality and similarity) or algorithms (e.g., community detection) can be used to assess the utility of a node to deliver a content or bring it closer to the destination.