Recent advances in mobile technologies have enabled a plethora of new applications. The hardware capabilities of mobile devices, however, are still insufficient for real-time stream data processing (e.g., real-time video stream). In order to process real-time streaming data, most existing applications offload the data and computation to a remote cloud service, such as Apache Storm or Apache Spark Streaming. Offloading streaming data, however, has high costs for users, e.g., significant service fees and battery consumption. To address these challenges, we design, implement and evaluate Mobile Storm, the first stream processing platform for mobile clouds, leveraging clusters of local mobile devices to process real-time stream data. In Mobile Storm, we model the workflow of a real-time stream processing job and decompose it into several tasks so that the job can be executed concurrently and in a distributed manner on multiple mobile devices. Mobile Storm was implemented on Android phones and evaluated extensively through a real-time HD video processing application. The result shows that Mobile Storm effectively processes HD Video Stream in a mobile cloud, which would be impossible on a single mobile device.
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机译：移动技术的最新进展已启用了许多新应用程序。然而，移动设备的硬件能力仍然不足以进行实时流数据处理（例如，实时视频流）。为了处理实时流数据，大多数现有应用程序将数据和计算卸载到远程云服务，例如Apache Storm或Apache Spark Streaming。但是，分流数据流给用户带来了高昂的成本，例如高昂的服务费和电池消耗。为了应对这些挑战，我们设计，实施和评估Mobile Storm，这是第一个用于移动云的流处理平台，它利用本地移动设备的群集来处理实时流数据。在Mobile Storm中，我们对实时流处理作业的工作流程进行建模，并将其分解为多个任务，以便可以在多个移动设备上同时并以分布式方式执行该作业。 Mobile Storm在Android手机上实现，并通过实时高清视频处理应用程序进行了广泛的评估。结果表明，Mobile Storm有效地处理了移动云中的高清视频流，这在单个移动设备上是不可能的。
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