5,328 research outputs found

    Improving BitTorrent's Peer Selection For Multimedia Content On-Demand Delivery

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    The great efficiency achieved by the BitTorrent protocol for the distribution of large amounts of data inspired its adoption to provide multimedia content on-demand delivery over the Internet. As it is not designed for this purpose, some adjustments have been proposed in order to meet the related QoS requirements like low startup delay and smooth playback continuity. Accordingly, this paper introduces a BitTorrent-like proposal named as Quota-Based Peer Selection (QBPS). This proposal is mainly based on the adaptation of the original peer-selection policy of the BitTorrent protocol. Its validation is achieved by means of simulations and competitive analysis. The final results show that QBPS outperforms other recent proposals of the literature. For instance, it achieves a throughput optimization of up to 48.0% in low-provision capacity scenarios where users are very interactive.Comment: International Journal of Computer Networks & Communications(IJCNC) Vol.7, No.6, November 201

    Analyzing Peer Selection Policies for BitTorrent Multimedia On-Demand Streaming Systems in Internet

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    The adaptation of the BitTorrent protocol to multimedia on-demand streaming systems essentially lies on the modification of its two core algorithms, namely the piece and the peer selection policies, respectively. Much more attention has though been given to the piece selection policy. Within this context, this article proposes three novel peer selection policies for the design of BitTorrent-like protocols targeted at that type of systems: Select Balanced Neighbour Policy (SBNP), Select Regular Neighbour Policy (SRNP), and Select Optimistic Neighbour Policy (SONP). These proposals are validated through a competitive analysis based on simulations which encompass a variety of multimedia scenarios, defined in function of important characterization parameters such as content type, content size, and client interactivity profile. Service time, number of clients served and efficiency retrieving coefficient are the performance metrics assessed in the analysis. The final results mainly show that the novel proposals constitute scalable solutions that may be considered for real project designs. Lastly, future work is included in the conclusion of this paper.Comment: 19 PAGE

    In-Network View Synthesis for Interactive Multiview Video Systems

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    To enable Interactive multiview video systems with a minimum view-switching delay, multiple camera views are sent to the users, which are used as reference images to synthesize additional virtual views via depth-image-based rendering. In practice, bandwidth constraints may however restrict the number of reference views sent to clients per time unit, which may in turn limit the quality of the synthesized viewpoints. We argue that the reference view selection should ideally be performed close to the users, and we study the problem of in-network reference view synthesis such that the navigation quality is maximized at the clients. We consider a distributed cloud network architecture where data stored in a main cloud is delivered to end users with the help of cloudlets, i.e., resource-rich proxies close to the users. In order to satisfy last-hop bandwidth constraints from the cloudlet to the users, a cloudlet re-samples viewpoints of the 3D scene into a discrete set of views (combination of received camera views and virtual views synthesized) to be used as reference for the synthesis of additional virtual views at the client. This in-network synthesis leads to better viewpoint sampling given a bandwidth constraint compared to simple selection of camera views, but it may however carry a distortion penalty in the cloudlet-synthesized reference views. We therefore cast a new reference view selection problem where the best subset of views is defined as the one minimizing the distortion over a view navigation window defined by the user under some transmission bandwidth constraints. We show that the view selection problem is NP-hard, and propose an effective polynomial time algorithm using dynamic programming to solve the optimization problem. Simulation results finally confirm the performance gain offered by virtual view synthesis in the network

    Exploitation of Novel Multiplayer Gesture-based Interaction and Virtual Puppetry for Digital Storytelling to Develop Children’s Narrative Skills

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    In recent years, digital storytelling has demonstrated powerful pedagogical functions by improving creativity, collaboration and intimacy among young children. Saturated with digital media technologies in their daily lives, the young generation demands natural interactive learning environments which offer multimodalities of feedback and meaningful immersive learning experiences. Virtual puppetry assisted storytelling system for young children, which utilises depth motion sensing technology and gesture control as the Human-Computer Interaction (HCI) method, has been proved to provide natural interactive learning experience for single player. In this paper, we designed and developed a novel system that allows multiple players to narrate, and most importantly, to interact with other characters and interactive virtual items in the virtual environment. We have conducted one user experiment with four young children for pedagogical evaluation and another user experiment with five postgraduate students for system evaluation. Our user study shows this novel digital storytelling system has great potential to stimulate learning abilities of young children through collaboration tasks

    Network Traffic Adaptation For Cloud Games

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    With the arrival of cloud technology, game accessibility and ubiquity have a bright future; Games can be hosted in a centralize server and accessed through the Internet by a thin client on a wide variety of devices with modest capabilities: cloud gaming. However, current cloud gaming systems have very strong requirements in terms of network resources, thus reducing the accessibility and ubiquity of cloud games, because devices with little bandwidth and people located in area with limited and unstable network connectivity, cannot take advantage of these cloud services. In this paper we present an adaptation technique inspired by the level of detail (LoD) approach in 3D graphics. It delivers multiple platform accessibility and network adaptability, while improving user's quality of experience (QoE) by reducing the impact of poor and unstable network parameters (delay, packet loss, jitter) on game interactivity. We validate our approach using a prototype game in a controlled environment and characterize the user QoE in a pilot experiment. The results show that the proposed framework provides a significant QoE enhancement

    Interactivity-Constrained Server Provisioning in Large-Scale Distributed Virtual Environments

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    Maintaining interactivity is one of the key challenges in distributed virtual environments (DVEs). In this paper, we consider a new problem, termed the interactivity-constrained server provisioning problem, whose goal is to minimize the number of distributed servers needed to achieve a prespecified level of interactivity. We identify and formulate two variants of this new problem and show that they are both NP-hard via reductions to the set covering problem. We then propose several computationally efficient approximation algorithms for solving the problem. The main algorithms exploit dependencies among distributed servers to make provisioning decisions. We conduct extensive experiments to evaluate the performance of the proposed algorithms. Specifically, we use both static Internet latency data available from prior measurements and topology generators, as well as the most recent, dynamic latency data collected via our own large-scale deployment of a DVE performance monitoring system over PlanetLab. The results show that the newly proposed algorithms that take into account interserver dependencies significantly outperform the well-established set covering algorithm for both problem variants

    A Multi-Agent Architecture for An Intelligent Web-Based Educational System

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    An intelligent educational system must constitute an adaptive system built on multi-agent system architecture. The multi-agent architecture component provides self-organization, self-direction, and other control functionalities that are crucially important for an educational system. On the other hand, the adaptiveness of the system is necessary to provide customization, diversification, and interactional functionalities. Therefore, an educational system architecture that integrates multi-agent functionality [50] with adaptiveness can offer the learner the required independent learning experience. An educational system architecture is a complex structure with an intricate hierarchal organization where the functional components of the system undergo sophisticated and unpredictable internal interactions to perform its function. Hence, the system architecture must constitute adaptive and autonomous agents differentiated according to their functions, called multi-agent systems (MASs). The research paper proposes an adaptive hierarchal multi-agent educational system (AHMAES) [51] as an alternative to the traditional education delivery method. The document explains the various architectural characteristics of an adaptive multi-agent educational system and critically analyzes the system’s factors for software quality attributes
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