Demo: DeLorean: using speculation to enable low-latency continuous interaction for mobile cloud gaming
Demo: DeLorean: using speculation to enable low-latency continuous interaction for mobile cloud gaming
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DOI：
10.1145/2594368.2601474
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发表时间：
2014-06
期刊：
影响因子：
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通讯作者：
Kyungmin Lee;David Chu;Eduardo Cuervo;A. Wolman;J. Flinn
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文献类型：
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作者：
Kyungmin Lee;David Chu;Eduardo Cuervo;A. Wolman;J. Flinn
在移动的设备上玩游戏非常流行。最近，云游戏-其中数据中心服务器代表瘦客户端执行游戏，瘦客户端仅传输UI输入事件并显示由服务器呈现的输出-已经成为传统客户端游戏执行的有趣替代方案。云游戏即服务（GaaS）为移动的客户端提供了几个突出的优势。首先，使用低端设备的用户可以获得与使用高端设备的用户相同的高质量体验。其次，移动的游戏开发者避免了移动的设备的巨大多样性带来的两个挑战：平台兼容性问题和每个平台的性能调整。第三，升级服务器（例如，用于bug修复、游戏更新等）比向客户端重新部署新软件要容易得多。最后，玩家可以从一个庞大的游戏库中进行选择，并立即玩其中任何一个。然而，移动的设备上的GaaS面临着一个关键的技术困境：面对广域延迟，玩家如何实现实时交互？实时交互性意味着客户端输入事件应快速反映在客户端显示屏上。用户研究表明，玩家对低至60 ms的延迟敏感，并且在延迟超过100 ms时加重[1]。从150 ms到250 ms的进一步延迟降低了75%的用户参与度[2]。相反，我们建议通过推测执行来减轻广域延迟。我们目前DeLorean的系统，提供实时游戏交互的速度与传统的本地客户端执行，尽管与网络延迟。DeLorean的基本方法将输入预测与推测执行相结合，以呈现可能在未来RTT毫秒内发生的多个可能的帧输出。DeLorean采用以下技术来实现这一点。未来投入预测：鉴于用户的历史倾向和最近的行为，我们表明，某些类别的用户行为是高度可预测的。我们开发了一个基于马尔可夫的预测模型，检查最近的用户输入预测预期的未来输入。我们使用两种技术来提高预测质量：输入事件的超级搜索，
Playing games on mobile devices is very popular. Recently, cloud gaming – where datacenter servers execute the games on behalf of thin clients that merely transmit UI input events and display output rendered by the servers – has emerged as an interesting alternative to traditional clientside game execution. Cloud Gaming-as-a-Service (GaaS) offers several advantages salient to mobile clients. First, users with low end devices can get the same high quality experience as users with high end devices. Second, mobile game developers avoid two challenges that arise with the huge diversity of mobile devices: platform compatibility headaches and per-platform performance tuning. Third, upgrading servers (e.g., for bug fixes, game updates, etc.) becomes far easier than redeploying new software to clients. Finally, players can select from a vast library of games and instantly play any of them. However, GaaS on mobile devices faces a key technical dilemma: how can players attain real-time interactivity in the face of wide-area latency? Real-time interactivity means client input events should be quickly reflected on the client display. User studies have shown that players are sensitive to as little as 60 ms latency, and are aggravated at latencies in excess of 100 ms [1]. A further delay degradation from 150 ms to 250 ms lowers user engagement by 75% [2]. Instead, we propose to mitigate wide-area latency via speculative execution. We present DeLorean a system that delivers real-time gaming interactivity as fast as traditional local client-side execution, despite with network latencies. DeLorean’s basic approach combines input prediction with speculative execution to render mulitple possible frame outputs which could occur RTT milliseconds in the future. DeLorean employs the following techniques to accomplish this. Future Input Prediction: Given the user’s historical tendencies and recent behavior, we show that some categories of user actions are highly predictable. We develop a Markovbased prediction model that examines recent user input to forecast expected future input. We use two techniques to improve prediction quality: supersampling of input events,