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On the MDP-Based Cost Minimization for Video-on-Demand Services in a Heterogeneous Wireless Network with Multihomed Terminals

机译:基于MDP的多宿主终端异构无线网络中视频点播业务的成本最小化

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In this paper, we deal with a cost minimization problem for a multihomed mobile terminal that downloads and plays a video-on-demand (VoD) stream. The cost consists of the user's dissatisfaction due to playback disruptions and communication cost for downloading the VoD stream. There are three components in our approach: parameter estimation, threshold adjustment, and threshold compensation. Since we do not assume any a priori knowledge about underlying random variables, necessary parameter values are estimated online. Using the resultant estimates, we formulate the problem as a Markov decision process (MDP) problem considering as if the random variables are exponentially distributed. To solve the MDP problem efficiently, we propose a threshold adjustment algorithm that exploits some structural properties of any optimal solution that are specific to our problem. Finally, to handle the cases where the random variables are not exponentially distributed, we propose a threshold compensation algorithm to compensate for the modeling error. Through extensive simulations, we compare the performance of our scheme with those of static threshold schemes.
机译:在本文中,我们处理了下载并播放视频点播(VoD)流的多宿主移动终端的成本最小化问题。成本包括由于回放中断而导致的用户不满以及下载VoD流的通信成本。我们的方法包括三个部分:参数估计,阈值调整和阈值补偿。由于我们不假设有关基础随机变量的任何先验知识,因此必须在线估算必要的参数值。使用所得的估计值,我们将问题公式化为考虑随机变量呈指数分布的马尔可夫决策过程(MDP)问题。为了有效地解决MDP问题,我们提出了一种阈值调整算法,该算法利用了针对我们问题的任何最佳解决方案的某些结构特性。最后,为处理随机变量未呈指数分布的情况,我们提出了一种阈值补偿算法来补偿建模误差。通过广泛的模拟,我们将方案的性能与静态阈值方案的性能进行了比较。

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