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. In the latter, we examine the impact of very small buffers when both real-time and TCP traffic coexist in the network.

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.

Delay is a key Internet performance metric and its stability, variation, and abrupt changes have been well studied.
However, little could have been said about the Internet-wide delay distribution. In order to build a representative sample set for the Internet-wide delay distribution, one needs to draw data from a random selection of source hosts to destination hosts and there is no measurement system with access to every AS and subnet of the Internet. In this work we propose to apply the path-stitching algorithm to archival measurement data and reconstruct the past history of Internet delay distribution. The two main advantages of path stitching are that data from existing measurement projects is sufficient to provide accurate estimates and it produces delay estimates between almost any two hosts in the Internet.

Logged messages are invaluable for debugging and diagnosing problems. Unfortunately, many execution logs are inscrutable in their raw form. For example, a production Google system may generate a billion-line log file in a single day. In my talk, I will detail two log-analysis tools that I developed to deal with this problem. These tools infer concise and precise models from large execution logs of sequential and distributed systems. Both tools enable new kinds of program analyses and make logs more useful to developers.

Wireless communication for intelligent transportation systems (ITSs) is a promising technology to improve driving safety, reduce traffic congestion and support information services in vehicles. A new era of vehicular networks that include vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communications is approaching.

BitTorrent is currently the dominant Peer-to-Peer (P2P) protocol for file-sharing applications. BitTorrent is also a nightmare for ISPs due to its network agnostic nature, which is responsible for high network transit costs. The research community has deployed a number of strategies for BitTorrent traffic localization, mostly relying on the communication between the peers and a central server called tracker. However, BitTorrent users have been abandoning the trackers in favor of distributed tracking based upon Distributed Hash Tables (DHTs).
 

Give the attendees an evolutionary view on the access networks and open perspectives on the potential developments upcoming. It will always keep an eye on the standardization trends and other ecosystem parameters (as regulation, cost and timeline constrains) in order to provide the attendees the background to further perceive some of the upcoming opted solutions and dynamics.