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Scheduling policy analysis of cloud video service

机译:云视频服务的调度策略分析

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As a leader in providing video service in US, Comcast provides cloud video service to Americans. Currently, the primary legal interpretation approving cloud video recording in cable-vision decision relies on individual copies for each video recorded. This means every recorded video in the cloud needs its own copy in the data center. Categorizing users by the estimated similar behavior is proposed manage the 20 billions videos available to around 50 millions subscribers. In this system, the subscribers with similar behavior are grouped in one cluster. Cloud recording cable video and IP video service requests are asynchronous and stored in two queues. The cluster goes to sleep if neither queue has requests. The cluster wakes up when a new request arrives. The cluster takes heterogeneous service calls: recording cable video and IP video. In this paper, a 2-class Markov Geo/G/1/K vacation model is presented to analyze the scheduling policy of processing two queues.
机译:作为美国提供视频服务的领导者,康卡斯特(Comcast)为美国人提供云视频服务。当前,在有线视觉决策中批准云视频记录的主要法律解释依赖于每个记录的视频的单独副本。这意味着云中的每个录制视频都需要在数据中心中拥有自己的副本。建议通过估计的类似行为对用户进行分类,以管理约5000万订户可用的200亿个视频。在该系统中,具有类似行为的订户被分组在一个集群中。云记录电缆视频和IP视频服务请求是异步的,并存储在两个队列中。如果两个队列都没有请求,则集群将进入睡眠状态。当新请求到达时,集群将唤醒。集群接受异构服务呼叫:记录有线视频和IP视频。本文提出了一种两类马尔可夫Geo / G / 1 / K休假模型来分析处理两个队列的调度策略。

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