Interest in real-time systems has grown considerably over recent years, primarily due to significant increase in the use of smart technologies and latency-sensitive applications such as cloud gaming, audio/video streaming, and smart homes. Significant work has been done on resource mapping in the cloud environment, and a number of promising results have been established accordingly where the focus is mainly on resource provisioning. However, the applicability of cloud computing services for real-time systems generated from smart systems is still in its infancy and remains unexplored, relatively. To address this gap, we propose a model for the smart systems that periodically offload computational workload to the cloud environment where virtual machines are allocated according to rate-monotonic scheduling policy to ensure requests are processed within the associated deadlines. Deadlines of tasks have been relaxed to improve server utilization as well as maintain a level of confidence in the timing constrains. Experimental results are discussed to highlight the applicability of static priority assignment for the workload in the context of virtual machines allocation.

中文翻译：

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在云环境中部署实时系统

近年来，人们对实时系统的兴趣显着增长，这主要是由于智能技术和延迟敏感应用程序（如云游戏、音频/视频流和智能家居）的使用显着增加。在云环境中的资源映射方面已经做了大量工作，并相应地建立了一些有希望的结果，其中重点主要是资源供应。然而，云计算服务对智能系统生成的实时系统的适用性仍处于起步阶段，相对而言仍有待探索。为了弥补这一差距，我们为智能系统提出了一个模型，该模型定期将计算工作量卸载到云环境，其中根据速率单调调度策略分配虚拟机，以确保在相关的截止日期内处理请求。任务的截止日期已放宽，以提高服务器利用率并保持对时间限制的信心水平。讨论了实验结果，以强调静态优先级分配在虚拟机分配环境中对工作负载的适用性。