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Energy-aware collaborative sensing for multiple applications in mobile cloud computing

机译:用于移动云计算中多种应用的能源感知协作感测

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Modern mobile handsets and the myriad of wearable devices connected to them offer a wide range of sensing capabilities. The ubiquity of such sensing devices offers the potential to realise novel applications based on collaborative sensing, in which application logic makes use of sensor input from a number of handsets, typically distributed across a defined physical area. Such applications will be enabled by mobile cloud computing, with the devices transferring raw or pre-processed sensed data to application logic hosted in the cloud. This results in a trade-off between the quality of the sensed data received by applications and the energy required to transfer data from the mobile handsets. We address this tradeoff by considering a scheme in which a collaborative sensing middleware mediates between multiple applications requiring sensed data and the mobile handsets located within a particular physical area. We present and evaluate an algorithm which seeks to maximise the degree to which sensed data transferred from a given mobile device can be served to more than one application. We show that this algorithm leads to better overall performance in terms of energy used than an algorithm which does not aggregate sensed information between applications.
机译:现代手机以及与之相连的众多可穿戴设备提供了广泛的传感功能。这样的感测设备的普遍存在提供了基于协同感测实现新颖应用的潜力,其中应用逻辑利用了来自通常分布在定义的物理区域上的多个手机的传感器输入。此类应用将通过移动云计算来实现,设备将原始或预处理的感测数据传输到云中托管的应用逻辑。这导致在应用接收的感测数据的质量与从移动手机传输数据所需的能量之间进行权衡。我们通过考虑一种方案来解决这一折衷,在方案中,协作感测中间件在需要感测数据的多个应用程序与位于特定物理区域内的移动手机之间进行中介。我们提出并评估了一种算法,该算法试图最大化从给定移动设备传输的感测数据可以服务于多个应用程序的程度。我们证明,与不聚合应用程序之间的感测信息的算法相比,该算法在能源消耗方面具有更好的整体性能。

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