463 research outputs found
A Comprehensive Analysis of Swarming-based Live Streaming to Leverage Client Heterogeneity
Due to missing IP multicast support on an Internet scale, over-the-top media
streams are delivered with the help of overlays as used by content delivery
networks and their peer-to-peer (P2P) extensions. In this context,
mesh/pull-based swarming plays an important role either as pure streaming
approach or in combination with tree/push mechanisms. However, the impact of
realistic client populations with heterogeneous resources is not yet fully
understood. In this technical report, we contribute to closing this gap by
mathematically analysing the most basic scheduling mechanisms latest deadline
first (LDF) and earliest deadline first (EDF) in a continuous time Markov chain
framework and combining them into a simple, yet powerful, mixed strategy to
leverage inherent differences in client resources. The main contributions are
twofold: (1) a mathematical framework for swarming on random graphs is proposed
with a focus on LDF and EDF strategies in heterogeneous scenarios; (2) a mixed
strategy, named SchedMix, is proposed that leverages peer heterogeneity. The
proposed strategy, SchedMix is shown to outperform the other two strategies
using different abstractions: a mean-field theoretic analysis of buffer
probabilities, simulations of a stochastic model on random graphs, and a
full-stack implementation of a P2P streaming system.Comment: Technical report and supplementary material to
http://ieeexplore.ieee.org/document/7497234
Computing system reliability modeling, analysis, and optimization
Ph.DDOCTOR OF PHILOSOPH
Diseño centrado en calidad para la difusión Peer-to-Peer de video en vivo
El uso de redes Peer-to-Peer (P2P) es una forma escalable para ofrecer servicios de video sobre Internet. Este documento hace foco en la definición, desarrollo y evaluación de una arquitectura P2P para distribuir video en vivo. El diseño global de la red es guiado por la calidad de experiencia (Quality of Experience - QoE), cuyo principal componente en este caso es la calidad del video percibida por los usuarios finales, en lugar del tradicional diseño basado en la calidad de servicio (Quality of Service - QoE) de la mayoría de los sistemas. Para medir la calidad percibida del video, en tiempo real y automáticamente, extendimos la recientemente propuesta metodología Pseudo-Subjective Quality Assessment (PSQA). Dos grandes líneas de investigación son desarrolladas. Primero, proponemos una técnica de distribución de video desde múltiples fuentes con las características de poder ser optimizada para maximizar la calidad percibida en contextos de muchas fallas y de poseer muy baja señalización (a diferencia de los sistemas existentes). Desarrollamos una metodología, basada en PSQA, que nos permite un control fino sobre la forma en que la señal de video es dividida en partes y la cantidad de redundancia agregada, como una función de la dinámica de los usuarios de la red. De esta forma es posible mejorar la robustez del sistema tanto como sea deseado, contemplando el límite de capacidad en la comunicación. En segundo lugar, presentamos un mecanismo estructurado para controlar la topología de la red. La selección de que usuarios servirán a que otros es importante para la robustez de la red, especialmente cuando los usuarios son heterogéneos en sus capacidades y en sus tiempos de conexión.Nuestro diseño maximiza la calidad global esperada (evaluada usando PSQA), seleccionado una topología que mejora la robustez del sistema. Además estudiamos como extender la red con dos servicios complementarios: el video bajo demanda (Video on Demand - VoD) y el servicio MyTV. El desafío en estos servicios es como realizar búsquedas eficientes sobre la librería de videos, dado al alto dinamismo del contenido. Presentamos una estrategia de "caching" para las búsquedas en estos servicios, que maximiza el número total de respuestas correctas a las consultas, considerando una dinámica particular en los contenidos y restricciones de ancho de banda. Nuestro diseño global considera escenarios reales, donde los casos de prueba y los parámetros de configuración surgen de datos reales de un servicio de referencia en producción. Nuestro prototipo es completamente funcional, de uso gratuito, y basado en tecnologías bien probadas de código abierto
Private Communication Detection via Side-Channel Attacks
Private communication detection (PCD) enables an ordinary network user to discover communication patterns (e.g., call time, length, frequency, and initiator) between two or more private parties. Analysis of communication patterns between private parties has historically been a powerful tool used by intelligence, military, law-enforcement and business organizations because it can reveal the strength of tie between these parties. Ordinary users are assumed to have neither eavesdropping capabilities (e.g., the network may employ strong anonymity measures) nor the legal authority (e.g. no ability to issue a warrant to network providers) to collect private-communication records. We show that PCD is possible by ordinary users merely by sending packets to various network end-nodes and analyzing the responses. Three approaches for PCD are proposed based on a new type of side channels caused by resource contention, and defenses are proposed. The Resource-Saturation PCD exploits the resource contention (e.g., a fixed-size buffer) by sending carefully designed packets and monitoring different responses. Its effectiveness has been demonstrated on three commercial closed-source VoIP phones. The Stochastic PCD shows that timing side channels in the form of probing responses, which are caused by distinct resource-contention responses when different applications run in end nodes, enable effective PCD despite network and proxy-generated noise (e.g., jitter, delays). It was applied to WiFi and Instant Messaging for resource contention in the radio channel and the keyboard, respectively. Similar analysis enables practical Sybil node detection. Finally, the Service-Priority PCD utilizes the fact that 3G/2G mobile communication systems give higher priority to voice service than data service. This allows detection of the busy status of smartphones, and then discovery of their call records by correlating the busy status. This approach was successfully applied to iPhone and Android phones in AT&T's network. An additional, unanticipated finding was that an Internet user could disable a 2G phone's voice service by probing it with short enough intervals (e.g., 1 second). PCD defenses can be traditional side-channel countermeasures or PCD-specific ones, e.g., monitoring and blocking suspicious periodic network traffic
Video streaming over the internet using application layer multicast
Multicast is a very important communication paradigm. However, the deployment of multicast at IP layer is very slow, due to development and deployment issues such as ISPs' lack of incentives to update routers and inter-operability among multicast routing protocols. Application Layer Multicast (ALM) is a good alternative, where participating peers organize themselves into a logical overlay network atop the physical links and data is \tunneled" to each other via unicast links. The distinctive feature between IP multicast and ALM is that in ALM, data replication and forwarding functionalities are performed by participating peers (a.k.a. end systems), rather than the routers in Internet Protocol (IP) multicast. This fundamental difference enables ALM to be able to circumvent the development and deployment issues of IP multicast, by exploiting the resources (e.g., CPU cycles, storage, and access bandwidth) at the edge of the network. Nevertheless, it also raises other challenges, as peers are not as stable as routers since they may join and depart the on-going session at will. In this thesis, we address some of the challenges and they are summarized as follows: First, most current P2P or ALM streaming systems are equipped with a non-scalable membership management algorithm, greatly hindering their applicability to large-scale implementations over the Internet: they either rely on a central entity to handle group membership, or simply assume that all group members are visible to each other and flooding is the main mechanism used to disseminate membership-related updates to all participating group members. This implies that they are only applicable to small groups. Second, one of ALM's prominent features, flexility, has not been fully exploited: moving the multicast functionalities from lower layer (IP layer) to higher layer (Application layer) can greatly facilitate the integration of Quality-of-Service (QoS) support. The end-to-end philosophy states that it is better to leave those functionalities to higher layers because the heterogeneity among users' requirements can be handled much better by end users, rather than the network. However, QoS, and in particular, reliability has not been thoroughly addressed in existing ALM schemes. Third, admission control algorithms are essential to the success of any ALM system, due to the fact that in ALM, each peer acts as both a client as well as a server. On the other hand, the heterogeneity among peers, in terms of their computational power, storage capacity, and access bandwidth, further complicates the design of a good admission control. Several contributions are made to address the aforementioned research challenges, and they are outlined as follows: The first contribution is a devised gossip-based membership management algorithm that is able to collect and disseminate membership-related information under high rate of churn, using relatively low communication overheads. The second contribution is a reliability-centric multicast tree construction algorithm that greatly enhance peers' perceived reliability. The third contribution is a QoS-aware tree construction algorithm that accommodates the heterogeneity among peers, such as access bandwidth, network distance, and reliability. The last contribution is the identification of the admission control problem in this overlay video streaming
Asynchronous Gossip for Averaging and Spectral Ranking
We consider two variants of the classical gossip algorithm. The first variant
is a version of asynchronous stochastic approximation. We highlight a
fundamental difficulty associated with the classical asynchronous gossip
scheme, viz., that it may not converge to a desired average, and suggest an
alternative scheme based on reinforcement learning that has guaranteed
convergence to the desired average. We then discuss a potential application to
a wireless network setting with simultaneous link activation constraints. The
second variant is a gossip algorithm for distributed computation of the
Perron-Frobenius eigenvector of a nonnegative matrix. While the first variant
draws upon a reinforcement learning algorithm for an average cost controlled
Markov decision problem, the second variant draws upon a reinforcement learning
algorithm for risk-sensitive control. We then discuss potential applications of
the second variant to ranking schemes, reputation networks, and principal
component analysis.Comment: 14 pages, 7 figures. Minor revisio
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