479 research outputs found

    ISP-friendly Peer-assisted On-demand Streaming of Long Duration Content in BBC iPlayer

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    In search of scalable solutions, CDNs are exploring P2P support. However, the benefits of peer assistance can be limited by various obstacle factors such as ISP friendliness - requiring peers to be within the same ISP, bitrate stratification - the need to match peers with others needing similar bitrate, and partial participation - some peers choosing not to redistribute content. This work relates potential gains from peer assistance to the average number of users in a swarm, its capacity, and empirically studies the effects of these obstacle factors at scale, using a month-long trace of over 2 million users in London accessing BBC shows online. Results indicate that even when P2P swarms are localised within ISPs, up to 88% of traffic can be saved. Surprisingly, bitrate stratification results in 2 large sub-swarms and does not significantly affect savings. However, partial participation, and the need for a minimum swarm size do affect gains. We investigate improvements to gain from increasing content availability through two well-studied techniques: content bundling - combining multiple items to increase availability, and historical caching of previously watched items. Bundling proves ineffective as increased server traffic from larger bundles outweighs benefits of availability, but simple caching can considerably boost traffic gains from peer assistance.Comment: In Proceedings of IEEE INFOCOM 201

    Study of the Topology Mismatch Problem in Peer-to-Peer Networks

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    The advantages of peer-to-peer (P2P) technology are innumerable when compared to other systems like Distributed Messaging System, Client-Server model, Cloud based systems. The vital advantages are not limited to high scalability and low cost. On the other hand the p2p system suffers from a bottle-neck problem caused by topology mismatch. Topology mismatch occurs in an unstructured peer-to-peer (P2P) network when the peers participating in the communication choose their neighbors in random fashion, such that the resultant P2P network mismatches its underlying physical network, resulting in a lengthy communication between the peers and redundant network traffics generated in the underlying network[1] However, most P2P system performance suffers from the mismatch between the overlays topology and the underlying physical network topology, causing a large volume of redundant traffic in the Internet slowing the performance. This paper surveys the P2P topology mismatch problems and the solutions adapted for different applications

    Energy aware and privacy preserving protocols for ad hoc networks with applications to disaster management

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    Disasters can have a serious impact on the functioning of communities and societies. Disaster management aims at providing efficient utilization of resources during pre-disaster (e.g. preparedness and prevention) and post-disaster (e.g. recovery and relief) scenarios to reduce the impact of disasters. Wireless sensors have been extensively used for early detection and prevention of disasters. However, the sensor\u27s operating environment may not always be congenial to these applications. Attackers can observe the traffic flow in the network to determine the location of the sensors and exploit it. For example, in intrusion detection systems, the information can be used to identify coverage gaps and avoid detection. Data source location privacy preservation protocols were designed in this work to address this problem. Using wireless sensors for disaster preparedness, recovery and relief operations can have high deployment costs. Making use of wireless devices (e.g. smartphones and tablets) widely available among people in the affected region is a more practical approach. Disaster preparedness involves dissemination of information among the people to make them aware of the risks they will face in the event of a disaster and how to actively prepare for them. The content is downloaded by the people on their smartphones and tablets for ubiquitous access. As these devices are primarily constrained by their available energy, this work introduces an energy-aware peer-to-peer file sharing protocol for efficient distribution of the content and maximizing the lifetime of the devices. Finally, the ability of the wireless devices to build an ad hoc network for capturing and collecting data for disaster relief and recovery operations was investigated. Specifically, novel energy-adaptive mechanisms were designed for autonomous creation of the ad hoc network, distribution of data capturing task among the devices, and collection of data with minimum delay --Abstract, page iii

    Raptorqp2P: Maximize The Performance Of P2P File Distribution With Raptorq Coding

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    BitTorrent is the most popular Peer-to-Peer (P2P) file sharing system widely used for distributing large files over the Internet. It has attracted extensive attentions from both network operators and researchers for investigating its deployment and performance. For example, recent studies have shown that under steady state, its rarest first scheme with the tit-for-tat mechanism can work very effectively and make BitTorrent near optimal for the generic file downloading process. However, in practice, the highly dynamic network environment, especially the notorious user churns prevalently existing in most peer-to-peer systems, can severely degrade the downloading performance. In this thesis, we first study on the limitations of BitTorrent under dynamic network environments, focusing on two scenarios where with our preliminary modeling and analysis, we clearly identify how network dynamics and peer churns can significantly degrade the performance. With these findings, we further propose a novel protocol named RaptorQP2P, which is based on RaptorQ coding, to overcome the limitations of current BitTorrent design and maximize the performance of P2P file distribution. The new protocol features two levels of RaptorQ encoding. At the top layer, the entire file is RaptorQ encoded to yield a collection of source blocks and repair blocks, and then each source and repair block is RaptorQ encoded independently to yield a collection of source symbols and repair symbols for the block. The symbols are independently transferred among the peers and when a sufficient number of distinct symbols for a particular block have been received, whether source or repair, the block can be reconstructed. The file can be reconstructed using a sufficient arbitrary number of distinct blocks. Our results show that RaptorQP2P can well handle the network dynamics as well as peer churns and significantly shorten the downloading completion time by up to 41.4% with excellent scalability on both file size and user population

    Video-on-Demand over Internet: a survey of existing systems and solutions

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    Video-on-Demand is a service where movies are delivered to distributed users with low delay and free interactivity. The traditional client/server architecture experiences scalability issues to provide video streaming services, so there have been many proposals of systems, mostly based on a peer-to-peer or on a hybrid server/peer-to-peer solution, to solve this issue. This work presents a survey of the currently existing or proposed systems and solutions, based upon a subset of representative systems, and defines selection criteria allowing to classify these systems. These criteria are based on common questions such as, for example, is it video-on-demand or live streaming, is the architecture based on content delivery network, peer-to-peer or both, is the delivery overlay tree-based or mesh-based, is the system push-based or pull-based, single-stream or multi-streams, does it use data coding, and how do the clients choose their peers. Representative systems are briefly described to give a summarized overview of the proposed solutions, and four ones are analyzed in details. Finally, it is attempted to evaluate the most promising solutions for future experiments. Résumé La vidéo à la demande est un service où des films sont fournis à distance aux utilisateurs avec u

    Optimizing on-demand resource deployment for peer-assisted content delivery

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    Increasingly, content delivery solutions leverage client resources in exchange for services in a pee-to-peer (P2P) fashion. Such peer-assisted service paradigm promises significant infrastructure cost reduction, but suffers from the unpredictability associated with client resources, which is often exhibited as an imbalance between the contribution and consumption of resources by clients. This imbalance hinders the ability to guarantee a minimum service fidelity of these services to clients especially for real-time applications where content can not be cached. In this thesis, we propose a novel architectural service model that enables the establishment of higher fidelity services through (1) coordinating the content delivery to efficiently utilize the available resources, and (2) leasing the least additional cloud resources, available through special nodes (angels) that join the service on-demand, and only if needed, to complement the scarce resources available through clients. While the proposed service model can be deployed in many settings, this thesis focuses on peer-assisted content delivery applications, in which the scarce resource is typically the upstream capacity of clients. We target three applications that require the delivery of real-time as opposed to stale content. The first application is bulk-synchronous transfer, in which the goal of the system is to minimize the maximum distribution time - the time it takes to deliver the content to all clients in a group. The second application is live video streaming, in which the goal of the system is to maintain a given streaming quality. The third application is Tor, the anonymous onion routing network, in which the goal of the system is to boost performance (increase throughput and reduce latency) throughout the network, and especially for clients running bandwidth-intensive applications. For each of the above applications, we develop analytical models that efficiently allocate the already available resources. They also efficiently allocate additional on-demand resource to achieve a certain level of service. Our analytical models and efficient constructions depend on some simplifying, yet impractical, assumptions. Thus, inspired by our models and constructions, we develop practical techniques that we incorporate into prototypical peer-assisted angel-enabled cloud services. We evaluate these techniques through simulation and/or implementation
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