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Selection and Aggregation of Location Information Provisioning Services

机译：位置信息供应服务的选择和聚合

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Aggregation of location estimates from multiple services for provisioning of location information enhances the accuracy and robustness of the final location information. Recent Internet of Things (IoT)-based localization service architectures therefore envision a "manager" for selecting and invoking provisioning services and, in the later step, aggregating the received information and providing it to location-based applications. The selection of provisioning services should take into account the accuracy and latency requirements from the applications and accuracy, latency, and power consumption characteristics of provisioning services. However, it is yet unclear how such selection should be made. We propose two algorithms for the selection of provisioning services aiming at meeting latency and subsequently accuracy requirements from the applications, one subject to minimizing per-request power consumption, while the other subject to a per-time bucket power minimization. In the considered examples, we show that the per-time bucket optimization achieves around 25% better performance in terms of power consumption, while trading-off accuracy satisfaction.
机译：从位置信息供应多种服务的位置估计聚集增强的最终位置信息的准确性和鲁棒性。因此，物联网（IOT）基于本地化服务架构的最新的互联网设想用于选择和调用供应服务，并在后面的步骤，汇总接收到的信息并提供给基于位置的应用的“经理”。的供应服务的选择应考虑到精度，并从应用程序和准确度，等待时间和供应服务的功耗特性的延迟要求。但是，目前还不清楚这种选择应该如何进行。我们提出了两种算法用于供应服务旨在满足从应用中的延迟，随后的精度要求，一个主题最大限度地减少每个请求的功耗的选择，而其他科目每一次桶，功耗最小化。在所考虑的例子中，我们表明，每一次斗优化实现了功耗方面的改进大约25％的性能，而交易过的准确性满意。

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