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首页> 外文会议>National Digital Games Research Conference: Trends, Technologies, and Applications;International Digital Games Research Conference: Trends, Technologies, and Applications >A Self-organizing Price-based Mechanism for Frame Rate Optimization in Cloud Gaming Networks Considering Quality of Experience
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A Self-organizing Price-based Mechanism for Frame Rate Optimization in Cloud Gaming Networks Considering Quality of Experience

机译：考虑体验质量的基于自组织价格的云游戏网络帧速率优化机制

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摘要

One of the most important issues in cloud services, especially in cloud gaming, is the limitations relevant to the hardware capabilities of end-users who are using mobile devices. In the cloud gaming terminology, the users who have poor resources are referred to as “Thin Clients”. On the other hand, cloud service providers should be able to provide minimum frame rate required by a computer game, simultaneously, to several thin clients at the same time, in such a way that meets the users' Quality of Experience (QoE). Generally, computer games have different degrees of render settings by default, in terms of three levels: high, medium, and low. These setting levels, in turn, can be translated into hardware and operating system capabilities, such as maximum textual details, brightness, contrast, and so on. Cloud game service providers use rendering settings as a means for transferring the frames of the game to thin clients. They also try to maximize their own profits with pricing on game frames. This paper addresses the subject of resource optimization using a pricing mechanism. The designed mechanism is able to allocate game frames in such a way that leads to achieving high user QoE and also maximizing the profit of the cloud server. We set the price of the frames considering their types. Each type has its own processor, memory, GPU requirements, etc. Our goal is to find the optimal combination of types for each user. Our proposed method is able to dynamically adapt itself to the requirements of both sides of the network. We also consider the scheduling issues of the cloud server in order to transfer the frames to the requested users. When the number of users is very high, the proposed mechanism applies the settings in such a way that the QoE is maintained at the desired level and the user's satisfaction is not violated at all. Simulation results show that the proposed priced-based approach attains lower bandwidth consumption values compared to the case in which no pricing mechanism is used. Also, the social welfare of the users is maximized.
机译：云服务（尤其是云游戏）中最重要的问题之一是与使用移动设备的最终用户的硬件功能有关的限制。在云游戏术语中，资源贫乏的用户称为“瘦客户端”。另一方面，云服务提供商应该能够同时满足多个瘦客户端同时满足多个用户的体验质量（QoE）的需求，同时提供计算机游戏所需的最低帧速率。通常，默认情况下，计算机游戏具有不同程度的渲染设置，分为三个级别：高，中和低。这些设置级别又可以转换为硬件和操作系统功能，例如最大的文本详细信息，亮度，对比度等等。云游戏服务提供商使用渲染设置作为将游戏框架传输到瘦客户端的一种方式。他们还尝试通过游戏框架定价来最大化自己的利润。本文探讨了使用定价机制进行资源优化的主题。设计的机制能够以导致实现高用户QoE的方式分配游戏框架，并最大程度地提高云服务器的利润。我们根据框架的类型设置框架的价格。每种类型都有自己的处理器，内存，GPU要求等。我们的目标是为每个用户找到最佳的类型组合。我们提出的方法能够动态地适应网络双方的需求。我们还考虑了云服务器的调度问题，以便将帧传输到请求的用户。当用户数量非常多时，所提出的机制将以这样的方式应用设置：将QoE维持在所需的水平，并且完全不会违反用户的满意度。仿真结果表明，与不使用定价机制的情况相比，所提出的基于定价的方法具有较低的带宽消耗值。而且，用户的社会福利被最大化。

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