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Performance bottleneck analysis and resource optimized distribution method for IoT cloud rendering computing system in cyber-enabled applications

机译:性能瓶颈分析和资源优化分配方法在网络应用中的IOT云渲染计算系统

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Abstract This paper analyzes current cloud computing, cloud rendering industry, and related businesses. In this field, cloud system performance lacks unified evaluation criterion. A novel analysis method and a related measure of cloud rendering system performance are presented in this paper. The main paper investigates the number of system concurrent users and average response delay about user access, average frame speed, system operation speed, and average response about user browsing system. This paper makes a theoretical analysis of a core business process about cloud rendering system, multi-task rendering processes especially. This paper analyzes the efficiency, average frame rate, rendering performance bottleneck of the cloud rendering system, and put forward a unique parameter adjustment strategy to improve system performance, by optimizing related server and rendering machine configuration. This paper puts forward a method to reduce the bottleneck of the system and prevent system performance deterioration in the new scheme. This paper puts forward a set of system optimization strategies to improve system performance. This is a new cloud rendering system performance optimization configuration scheme and optimization strategy.
机译:摘要本文分析了当前云计算,云渲染行业和相关业务。在此字段中,云系统性能缺乏统一的评估标准。本文提出了一种新的分析方法和云渲染系统性能的相关措施。主纸张调查系统并发用户的数量和关于用户访问,平均帧速,系统操作速度和关于用户浏览系统的平均响应的平均响应延迟。本文对云渲染系统,尤其是多任务渲染过程的核心业务流程进行了理论分析。本文分析了云渲染系统的效率,平均帧速率,渲染性能瓶颈,并提出了一种独特的参数调整策略,通过优化相关的服务器和渲染机器配置来提高系统性能。本文提出了一种方法来减少系统的瓶颈,防止新方案中的系统性能恶化。本文提出了一系列系统优化策略,以提高系统性能。这是一种新的云渲染系统性能优化配置方案和优化策略。

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