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F-MStorm: Feedback-Based Online Distributed Mobile Stream Processing

机译:F-MStorm:基于反馈的在线分布式移动流处理

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A distributed mobile stream processing system allows mobile devices to process stream data that exceeds any single device's computation capability without the help of infrastructure. It is paramount to have such a system in many critical application scenarios, such as military operations and disaster response, yet an efficient online mobile stream processing system is still missing. In this paper, we make the key observation that the unique characteristics of mobile stream processing call for a feedback-based system design, which is in sharp contrast with the static configuration and scheduling of the current mobile stream processing system, 'MStorm'. At first, we demonstrate the inefficiencies of MStorm through several real-world experiments. Then, we propose F-MStorm, a feedback-based online distributed mobile stream processing system, which adopts the feedback-based approach in the configuration, scheduling and execution levels of system design. We implement F-MStorm on Android phones and evaluate its performance through benchmark applications. We show that it achieves up to 3x lower response time, 10% higher throughput and consumes 23% less communication energy than the state-of-the-art systems.
机译:分布式移动流处理系统允许移动设备在不借助基础架构的情况下处理超出任何单个设备的计算能力的流数据。在许多关键的应用场景(例如军事行动和灾难响应)中拥有这样的系统至关重要,但是仍然缺少有效的在线移动流处理系统。在本文中,我们主要观察到,移动流处理的独特特性要求基于反馈的系统设计,这与当前移动流处理系统“ MStorm”的静态配置和调度形成鲜明对比。首先,我们通过几个实际实验来证明MStorm的效率低下。然后,我们提出了一种基于反馈的在线分布式移动流处理系统F-MStorm,它在系统设计的配置,调度和执行级别上采用了基于反馈的方法。我们在Android手机上实施F-MStorm,并通过基准测试应用程序评估其性能。我们证明,与最先进的系统相比,它的响应时间缩短了3倍,吞吐量提高了10%,通信能耗降低了23%。

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