Dynamic control of Coding in Delay Tolerant Networks

Delay tolerant Networks (DTNs) leverage the mobility of relay nodes to compensate for lack of permanent connectivity and thus enable communication between nodes that are out of range of each other. To decrease message delivery delay, the information to be transmitted is replicated in the network. We study replication mechanisms that include Reed-Solomon type codes as well as network coding in order to improve the probability of successful delivery within a given time limit. We propose an analytical approach that allows us to compute the probability of successful delivery. We study the effect of coding on the performance of the network while optimizing parameters that govern routing

Quelques Résultats sur les Codes LDPC Hybrides

Ce papier rassemble quelques résultats sur une nouvelle classe très générale de codes LDPC, nommés codes LDPC hybrides. Les symboles d'un mot de code LDPC hybride appartiennent à des ensembles finis d'ordres différents. On peut ainsi contrôler conjointement le couple (densité de branche, taille des symboles). Le condition de stabilité exposée dans ce papier permet d'identifier un avantage des codes LDPC hybrides sur les codes LDPC classique binaires et non-binaires. Une analyse de l'évolution de l'information mutuelle est menée, sous approximation gaussienne, en vue de concevoir de bons codes LDPC hybrides. Grâce au fait que l'on peut inclure des contraintes de taille finie dans l'optimisation, les simulations à tailles finies montrent que nos codes représentent un compromis intéressant entre bonnes performances en convergence et en plancher d'erreur. En particulier, pour un rendement de 1/6, le code LDPC hybride optimisé bat les meilleurs codes connus

User-Adaptive Editing for 360 degree Video Streaming with Deep Reinforcement Learning

International audienceThe development through streaming of 360°videos is persistently hindered by how much bandwidth they require. Adapting spatially the quality of the sphere to the user's Field of View (FoV) lowers the data rate but requires to keep the playback buffer small, to predict the user's motion or to make replacements to keep the buffered qualities up to date with the moving FoV, all three being uncertain and risky. We have previously shown that opportunistically regaining control on the FoV with active attention-driving techniques makes for additional levers to ease streaming and improve Quality of Experience (QoE). Deep neural networks have been recently shown to achieve best performance for video streaming adaptation and head motion prediction. This demo presents a step ahead in the important investigation of deep neural network approaches to obtain user-adaptive and network-adaptive 360°video streaming systems. In this demo, we show how snap-changes, an attention-driving technique, can be automatically modulated by the user's motion to improve the streaming QoE. The control of snap-changes is made with a deep neural network trained on head motion traces with the Deep Reinforcement Learning strategy A3C

Adaptive video streaming and multipath: can less be more?

International audienceA prominent portion of the traffic carried by In-ternet Service Providers (ISP) is delivered by Content Delivery Networks (CDNs). CDNs usually deploy their own caches at ISPs in addition to the servers deployed in their own premises. With the adoption of multipath transport protocols such as MPTCP, content consumers are able to retrieve their data from either caches deployed in their ISPs or server in the CDN premises using multiple paths in parallel. In this paper we present a study on the interplay between actors of a multipath-enabled video delivery system. For that we design a realistic numerical evaluation experiment; results obtained suggest that multipath can be both beneficial and harmful for ISP and CDN in different representative scenarios

An ns-3 distribution supporting MPTCP and MPEG-DASH obtained by merging community models

International audienceMPEG-DASH and MPTCP are two technologies growing in interest and put together they promise greater quality of experience for video consumers and better network resource usage. However, while independent MPEG-DASH and MPTCP implementations exist for ns-3, they are not directly usable together as they suffer from incompatibilities. In this work, we introduce a new ns-3 distribution that packages the AMuSt Framework DASH implementation and the ns-3 MPTCP implementation from University of Sussex such that they can be used together to nourish the flourishing research on Internet video streaming

Dynamic Control of Coding for Progressive Packet Arrivals in DTNs

International audienceDelay tolerant Networks (DTNs) leverage the mobility of relay nodes to compensate for lack of persistent connectivity. In order to decrease message delivery delay, the information to be transmitted can be replicated in the network. For general packet arrivals at the source and two-hop routing, we derive performance analysis of replication-based routing policies and study their optimization. In particular, we find out the conditions for optimality in terms of probability of successful delivery and mean delay and devise optimal policies, so-called piecewise threshold policies. We account for linear block-codes as well as rateless random linear coding to efficiently generate redundancy, as well as for an energy constraint in the optimization. We numerically assess the higher efficiency of piecewise threshold policies compared with other policies by developing heuristic optimization of the thresholds for all flavors of coding considered

Estimating File-Spread in Delay Tolerant Networks under Two-Hop Routing

Part 6: DTN and Wireless Sensor NetworksInternational audienceWe consider a Delay/Disruption Tolerant Network under two-hop routing. Our objective is to estimate and track the degree of spread of a message/file in the network. Indeed, having such real-time information is critical for on-line control of routing and energy expenditure. It also benefits the multi-casting application. With exponential inter-meeting times of mobile nodes: (i) for the estimation problem, we obtain exact expressions for the minimum mean-squared error (MMSE) estimator, and (ii) for the tracking problem, we first derive the diffusion approximations for the system dynamics and the measurements and then apply Kalman filtering. We also apply the solutions of the estimation and filtering problems to predict the time when a certain pre-defined fraction of nodes have received a copy of the message/file. Our analytical results are corroborated with extensive simulation results

Through the Eyes of Women in Engineering: An immersive VR experience

International audienceYoung women frequently face implicit behavioral biases – through unfriendly gaze, gestures, or speech – in all aspects of their daily lives. This is particularly true in the field of engineering, where women are a minority, making it emotionally difficult for them to fit in and feel at home, and deterring young women to enter these fields. Yet these systematic implicit biases are very hard to observe without being the target of such behavior and being accustomed to the current “norms” and “ways of acting” in the society. At their root is the misalignment between the stereotypes associated with femininity, and those associated with computer engineering − a misalignment whose keystone is how the gaze of others objectifies the body of women, and whose consequence and means of perpetuation is discomfort. Our objective is to create an interactive piece to communicate the discomfort of women in engineering, to tell their stories and expose this misalignment. To address this objective, we harness virtual reality to create an experience that embodies the user in the place of a woman character who travels through three common scenes in her life as an engineer. We design different gaze interactions, gestures, and speech styles that reflect common patterns for implicit behavioral biases, including objectification, isolation, and belittlement. The piece is an application that can be experienced in a headset or in a web browser

Research Proposal: Analyzing and Understanding Embodied Interactions in Virtual Reality Systems

International audienceVirtual reality (VR) offers opportunities in human-computer interaction research, to embody users in immersive environments and observe how they interact with 3D scenarios under well-controlled environments. VR content has stronger influences on users physical and emotional states as compared to traditional 2D media, however, a fuller understanding of this kind of embodied interaction is currently limited by the extent to which attention and behavior can be observed in a VR environment, and the accuracy at which these observations can be interpreted as, and mapped to, real-world interactions and intentions. This thesis aims at the creation of a system to help designers in the analysis of the entire user experience in VR environment: how they feel, what is their intentions when interacting with a certain object, provide them guidance based on their needs and attention. A controlled environment in which the user is guided will help to establish a better intersubjectivity between designer intention who created the experience and users who lived it and will lead to a more efficient analysis of the user behavior in VR systems for the design of better experiences. CCS CONCEPTS • Human-centered computing → Systems and tools for interaction design; • Computing methodologies → Virtual reality