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Resource Scheduling in Enhanced Pay-Per-View Continuous Media Databases

机译:增强型按次计费连续媒体数据库中的资源调度

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The enhanced pay-per-view (EPPV) model for providing continuous-media-on-demand (CMOD) services associates with each continuous media clip a display frequency that depends on the clip's popularity. The aim is to increase the number of clients that can be serviced concurrently beyond the capacity limitations of available resources, while guaranteeing a constraint on the response time. This is achieved by sharing periodic continuous media streams among multiple clients. In this paper, we provide a comprehensive study of the resource scheduling problems associated with supporting EPPV for continuous media clips with (possibly) different display rates, frequencies, and lengths. Our main objective is to maximize the amount of disk bandwidth that is effectively scheduled under the given data layout and storage constraints. This formulation gives rise to NP-hard combinatorial optimization problems that fall within the realm of hard real-time scheduling theory. Given the intractability of the problems, we propose novel heuristic solutions with polynomial-time complexity. Preliminary results from an experimental evaluation of the proposed schemes are also presented.
机译:用于提供按需连续媒体(CMOD)服务的增强的按次付费(EPPV)模型将每个连续媒体剪辑的显示频率与剪辑的受欢迎程度相关联。目的是增加可同时服务的客户端数量,使其超出可用资源的容量限制,同时保证对响应时间的限制。这是通过在多个客户端之间共享周期性的连续媒体流来实现的。在本文中,我们对与支持EPPV的(可能)显示速率,频率和长度不同的连续媒体剪辑的资源调度问题进行了全面研究。我们的主要目标是在给定的数据布局和存储约束下,最大化有效调度的磁盘带宽量。这种表述引起了NP-硬组合优化问题,这些问题属于硬实时调度理论的范畴。鉴于问题的棘手性,我们提出了具有多项式时间复杂度的新颖启发式解决方案。还提出了对所提出的方案进行实验评估的初步结果。

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