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首页> 外文期刊>IEEE Journal on Selected Areas in Communications >Effective Utilization of User Resources in PA-VoD Systems with Channel Heterogeneity
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Effective Utilization of User Resources in PA-VoD Systems with Channel Heterogeneity

机译:具有通道异质性的PA-VoD系统中用户资源的有效利用

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摘要

Nowadays, peer-assisted video on-demand (PA-VoD) systems offer high-definition (HD) channels to online users. However, the quality of service in such HD channels is usually not comparable to the standard-definition (SD) ones, as HD channels have to seek more bandwidth support and cache space from peers, which is a challenging task. In this paper, we focus on peer cache and upload bandwidth management at the same time for multi-channel PA-VoD systems with heterogeneous video playback rates, i.e., HD and SD channels coexist with different bandwidth and cache requirements. We first take user viewing behaviors into account and derive the statistical performance bounds on server bandwidth consumption, which lead to the conclusion that such behaviors can easily affect the provisioning for HD channels, even if there is enough upload bandwidth from SD peers. We then formulate bandwidth allocation as a linear programming problem to calculate the tight lower bound at any time instant, with global information available and system-wide coordination possible (e.g., through a tracker). Next, we design heuristic algorithms for peer cache replacement and upload bandwidth allocation to fit with the nature of a P2P structure, and the results are compared with the statistical and instance performance bounds through extensive simulation, which shows the efficacy of the proposed algorithms in dynamic scenarios.
机译:如今,对等辅助视频点播(PA-VoD)系统为在线用户提供高清(HD)频道。但是,这种高清频道的服务质量通常无法与标准清晰度(SD)的频道媲美,因为高清频道必须寻求更多的带宽支持和对等方的缓存空间,这是一项艰巨的任务。在本文中,对于具有异类视频播放速率的多通道PA-VoD系统,即HD和SD通道共存于不同的带宽和缓存要求,我们将同时关注对等缓存和上传带宽管理。我们首先考虑用户观看行为,并得出服务器带宽消耗的统计性能界限,这得出的结论是,即使SD对等端有足够的上传带宽,此类行为也很容易影响HD频道的设置。然后,我们将带宽分配公式化为线性规划问题,以在任何时刻获得可用的全局信息并可能进行系统范围的协调(例如通过跟踪器)来计算严格的下限。接下来,我们设计启发式算法来替换对等缓存并上传带宽分配,以适应P2P结构的性质,并通过广泛的仿真将结果与统计和实例性能范围进行比较,这表明了该算法在动态环境中的有效性场景。

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