26 research outputs found

    Static Web content distribution and request routing in a P2P overlay

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    The significance of collaboration over the Internet has become a corner-stone of modern computing, as the essence of information processing and content management has shifted to networked and Webbased systems. As a result, the effective and reliable access to networked resources has become a critical commodity in any modern infrastructure. In order to cope with the limitations introduced by the traditional client-server networking model, most of the popular Web-based services have employed separate Content Delivery Networks (CDN) to distribute the server-side resource consumption. Since the Web applications are often latency-critical, the CDNs are additionally being adopted for optimizing the content delivery latencies perceived by the Web clients. Because of the prevalent connection model, the Web content delivery has grown to a notable industry. The rapid growth in the amount of mobile devices further contributes to the amount of resources required from the originating server, as the content is also accessible on the go. While the Web has become one of the most utilized sources of information and digital content, the openness of the Internet is simultaneously being reduced by organizations and governments preventing access to any undesired resources. The access to information may be regulated or altered to suit any political interests or organizational benefits, thus conflicting with the initial design principle of an unrestricted and independent information network. This thesis contributes to the development of more efficient and open Internet by combining a feasibility study and a preliminary design of a peer-to-peer based Web content distribution and request routing mechanism. The suggested design addresses both the challenges related to effectiveness of current client-server networking model and the openness of information distributed over the Internet. Based on the properties of existing peer-to-peer implementations, the suggested overlay design is intended to provide low-latency access to any Web content without sacrificing the end-user privacy. The overlay is additionally designed to increase the cost of censorship by forcing a successful blockade to isolate the censored network from the rest of the Internet

    MDS-Coded Caching Leveraged by Coordinated Multi-Point Transmission

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    WiFi-Based Human Activity Recognition Using Attention-Based BiLSTM

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    Recently, significant efforts have been made to explore human activity recognition (HAR) techniques that use information gathered by existing indoor wireless infrastructures through WiFi signals without demanding the monitored subject to carry a dedicated device. The key intuition is that different activities introduce different multi-paths in WiFi signals and generate different patterns in the time series of channel state information (CSI). In this paper, we propose and evaluate a full pipeline for a CSI-based human activity recognition framework for 12 activities in three different spatial environments using two deep learning models: ABiLSTM and CNN-ABiLSTM. Evaluation experiments have demonstrated that the proposed models outperform state-of-the-art models. Also, the experiments show that the proposed models can be applied to other environments with different configurations, albeit with some caveats. The proposed ABiLSTM model achieves an overall accuracy of 94.03%, 91.96%, and 92.59% across the 3 target environments. While the proposed CNN-ABiLSTM model reaches an accuracy of 98.54%, 94.25% and 95.09% across those same environments

    Incentive-driven QoS in peer-to-peer overlays

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    A well known problem in peer-to-peer overlays is that no single entity has control over the software, hardware and configuration of peers. Thus, each peer can selfishly adapt its behaviour to maximise its benefit from the overlay. This thesis is concerned with the modelling and design of incentive mechanisms for QoS-overlays: resource allocation protocols that provide strategic peers with participation incentives, while at the same time optimising the performance of the peer-to-peer distribution overlay. The contributions of this thesis are as follows. First, we present PledgeRoute, a novel contribution accounting system that can be used, along with a set of reciprocity policies, as an incentive mechanism to encourage peers to contribute resources even when users are not actively consuming overlay services. This mechanism uses a decentralised credit network, is resilient to sybil attacks, and allows peers to achieve time and space deferred contribution reciprocity. Then, we present a novel, QoS-aware resource allocation model based on Vickrey auctions that uses PledgeRoute as a substrate. It acts as an incentive mechanism by providing efficient overlay construction, while at the same time allocating increasing service quality to those peers that contribute more to the network. The model is then applied to lagsensitive chunk swarming, and some of its properties are explored for different peer delay distributions. When considering QoS overlays deployed over the best-effort Internet, the quality received by a client cannot be adjudicated completely to either its serving peer or the intervening network between them. By drawing parallels between this situation and well-known hidden action situations in microeconomics, we propose a novel scheme to ensure adherence to advertised QoS levels. We then apply it to delay-sensitive chunk distribution overlays and present the optimal contract payments required, along with a method for QoS contract enforcement through reciprocative strategies. We also present a probabilistic model for application-layer delay as a function of the prevailing network conditions. Finally, we address the incentives of managed overlays, and the prediction of their behaviour. We propose two novel models of multihoming managed overlay incentives in which overlays can freely allocate their traffic flows between different ISPs. One is obtained by optimising an overlay utility function with desired properties, while the other is designed for data-driven least-squares fitting of the cross elasticity of demand. This last model is then used to solve for ISP profit maximisation
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