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Device-Centric Sensing: An Alternative to Data-Centric Approaches

机译：以设备为中心的传感：以数据为中心的方法的替代方法

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摘要

When pieces of information originate from the physical world through the sensing infrastructure, there is a pressing need to cope with the overhead and inherent limitations lying in merely shifting huge amounts of aggregated data across the net. In this scenario, a key point is the minimization of wasted bandwidth to accommodate for ever-growing demands of sensing data. For effective treatment of sensing data, BigData principles and approaches should be adopted, particularly the one by which computing has to be brought as near as possible to data. In this paper, we propose a new approach to deal with sensing data inspired by this principle, injecting intelligence on the device instead of just using it as source of data, thus reversing the trend from the current data-centric paradigm toward a device-centric one. This way, we shift the focus from the application level onto the infrastructure one, adopting a Cloud-oriented approach to abstract and virtualize sensor-hosting boards ready to be reconfigured with custom logic, such as MapReduce, by providing resources on demand, as a service. Theoretical, design, and technical aspects have been addressed in this paper through the evaluation of a device-centric sensing infrastructure-as-a-service (IaaS) stack implementation. In particular, a prototype for mobiles is described, getting into platform-dependent details where needed. The facilities so far implemented under the Android platform have been put under preliminary testing through a mobile application.
机译：当信息通过感测基础结构从物理世界中发出时，迫切需要解决开销和固有限制，即仅在网络上移动大量聚合数据。在这种情况下，关键点在于最小化带宽浪费，以适应不断增长的传感数据需求。为了有效处理感测数据，应采用BigData原理和方法，尤其是必须使计算尽可能接近数据的原理和方法。在本文中，我们提出了一种新方法来处理受此原理启发的感测数据，将智能注入设备上，而不只是将其用作数据源，从而将趋势从当前的以数据为中心的范式转向以设备为中心的趋势一。通过这种方式，我们将重点从应用程序级别转移到基础架构级别，采用一种面向云的方法来抽象化和虚拟化传感器托管板，准备通过自定义逻辑（例如MapReduce）通过按需提供资源来重新配置传感器托管板。服务。通过评估以设备为中心的传感基础设施即服务（IaaS）堆栈的实现，本文解决了理论，设计和技术方面的问题。特别地，描述了用于移动电话的原型，并在需要时进入与平台有关的细节。到目前为止，在Android平台下实现的功能已通过移动应用程序进行了初步测试。

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