Towards SVC-based adaptive streaming in information centric networks

HTTP Adaptive Streaming (HAS) is becoming the de-facto standard for video streaming services. In HAS, each video is segmented and stored in different qualities. The client can dynamically select the most appropriate quality level to download, allowing it to adapt to varying network conditions. As the Internet was not designed to deliver such applications, optimal support for multimedia delivery is still missing. Information Centric Networking (ICN) is a recently proposed disruptive architecture that could solve this issue, where the focus is given to the content rather than to end-to-end connectivity. Due to the bandwidth unpredictability typical of ICN, standard AVC-based HAS performs quality selection sub-optimally, thus leading to a poor Quality of Experience (QoE). In this article, we propose to overcome this inefficiency by using Scalable Video Coding (SVC) instead. We individuate the main advantages of SVC-based HAS over ICN and outline, both theoretically and via simulation, the research challenges to be addressed to optimize the delivered QoE

Performance Evaluation - Annual Report Year 3

This report describes the work done and results obtained in third year of the CATNETS project. Experiments carried out with the different configurations of the prototype are reported and simulation results are evaluated with the CATNETS metrics framework. The applicability of the Catallactic approach as market model for service and resource allocation in application layer networks is assessed based on the results and experience gained both from the prototype development and simulations. --Grid Computing

Multi-View Video Packet Scheduling

In multiview applications, multiple cameras acquire the same scene from different viewpoints and generally produce correlated video streams. This results in large amounts of highly redundant data. In order to save resources, it is critical to handle properly this correlation during encoding and transmission of the multiview data. In this work, we propose a correlation-aware packet scheduling algorithm for multi-camera networks, where information from all cameras are transmitted over a bottleneck channel to clients that reconstruct the multiview images. The scheduling algorithm relies on a new rate-distortion model that captures the importance of each view in the scene reconstruction. We propose a problem formulation for the optimization of the packet scheduling policies, which adapt to variations in the scene content. Then, we design a low complexity scheduling algorithm based on a trellis search that selects the subset of candidate packets to be transmitted towards effective multiview reconstruction at clients. Extensive simulation results confirm the gain of our scheduling algorithm when inter-source correlation information is used in the scheduler, compared to scheduling policies with no information about the correlation or non-adaptive scheduling policies. We finally show that increasing the optimization horizon in the packet scheduling algorithm improves the transmission performance, especially in scenarios where the level of correlation rapidly varies with time

Multi-Channel Two-way Time of Flight Sensor Network Ranging

Two-way time of flight (ToF) ranging is one of the most interesting approaches for localization in wireless sensor networking since previous ToF ranging approaches using commercial off-the-shelf (COTS) devices have achieved good accuracy. The COTS-based approaches were, however, evaluated only in line-of-sight conditions. In this paper, we extend ToF ranging using multiple IEEE 802.15.4 channels. Our results demonstrate that with multiple channels we can achieve good accuracy even in non line-of-sight conditions. Furthermore, our measurements suggest that the variance between different channels serves as a good estimate of the accuracy of the measurements, which can be valuable information for applications that require localization information

The Quest for Bandwidth Estimation Techniques for large-scale Distributed Systems

In recent years the research community has developed many techniques to estimate the end-to-end available bandwidth of an Internet path. This important metric has been proposed for use in several distributed systems and, more recently, has even been considered to improve the congestion control mechanism of TCP. Thus, it has been suggested that some existing estimation techniques could be used for this purpose. However, existing tools were not designed for large-scale deployments and were mostly validated in controlled settings, considering only one measurement running at a time. In this paper, we argue that current tools, while offering good estimates when used alone, might not work in large-scale systems where several estimations severely interfere with each other. We analyze the properties of the measurement paradigms employed today and discuss their functioning, study their overhead and analyze their interference. Our testbed results show that current techniques are insufficient as they are. Finally, we will discuss and propose some principles that should be taken into account for including available bandwidth measurements in large-scale distributed systems. 1

Valuing flexibility in the migration to flexgrid networks

Flexible optical networking can now be installed to increase network capacity in light of future traffic demands. This paper researches the different migration paths using a real option analysis, showing the impact of uncertainty