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

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.

Multimedia content delivery is projected to be the biggest bandwidth consumer of the future Internet. For many years, the mechanism for content delivery envisioned by the networking community is network multicast.

Multicasting emulates traditional TV broadcasting; it is designed to be network efficient. But it falls short in at least two aspects: (a) it does not maximize throughput for content delivery; (b) like TV broadcasting, it does not provide on-demand access (i.e. Video-on-Demand).

Embedded sensor systems are well suited to provide context data, i.e. any information which allows determining the context of entities (e.g. a user's location, an object's environmental parameters, or the number of people in a room). The additional integration of actuators allows interaction with the real world, e.g. control of heating, ventilation, or lighting. However, the big gap between the heterogeneous set of devices providing sensing and/or actuation needs to be bridged to enable smart context-aware applications. Special consideration hereby needs to be given to the efficient use of the available energy budget and the support for device heterogeneity. In this talk, means towards energy-efficient data transfer by applying header and payload compression for Wireless Sensor and Actuator Networks (WSAN) are presented, as well as our approach towards the seamless integration of WSAN nodes through using semantic self-descriptions and means towards unifying the access to node resources.

Improving the energy-efficiency of core routers is important for ISPs and equipment vendors alike. We tackle this problem by focusing on packet buffers in backbone router line-cards. We broadly classify the talk into two parts - an evolutionary approach and a clean-slate design. In the former, we propose a simple power saving mechanism that turns buffers on/off to save energy. Our scheme can be incrementally deployed today and requires minimal changes to existing line-card design.

This talk will introduce P2PSIP (Peer-to-peer Session Initiation Protocol) technologies, including the most common protocols and algorithms. The talk will also discuss the performance of these technologies in different network settings and the tradeoffs associated with deploying P2PSIP systems. Additionally, the talk will cover issues related to security and NAT traversal.

​We describe the design and implementation of DeepDive, a system for transparently identifying and managing performance interference between virtual machines (VMs) co-located on the same physical machine in Infrastructure-as-a-Service cloud environments.

DeepDive successfully addresses several important challenges, including the lack of performance information from applications, and the large overhead of detailed interference analysis. We first show that it is possible to use easily-obtainable, low-level metrics to clearly discern when interference is occurring and what resource is causing it. Next, using realistic workloads, we show that DeepDive quickly learns about interference across co-located VMs. Finally, we show DeepDive’s ability to deal efficiently with interference when it is detected, by using a low-overhead approach to identifying a VM placement that alleviates interference.