A low-power sensor polling for aggregated-task context on mobile devices
A low-power sensor polling for aggregated-task context on mobile devices
复制标题
移动设备上聚合任务上下文的低功耗传感器轮询
DOI：
10.1016/j.future.2019.02.027
复制
发表时间：
2019-09
期刊：
影响因子：
--
通讯作者：
Bing Guo
中科院分区：
文献类型：
--
作者：
Jihe Wang;Danghui Wang;Bing Guo
当前智能手机的传感器类型非常丰富，可以提供各种用户行为跟踪和社交网络共享，即无处不在的社交网络应用。由于每个移动的应用总是无限制地激活相关的传感器，因此传感器功耗占系统总功率预算的很大一部分。更糟糕的是，智能手机内的传感器通常以全频率激活，以匹配一组聚合任务的刷新率，称为基于全轮询的检测，这导致传感器上的大量不必要活动和快速电池消耗。在这项工作中，我们提出了一个低功耗的传感器轮询策略的移动的应用程序，动态地删除不必要的传感器活动。通过这种设计，无关的传感器可以保持更长时间的睡眠状态。为了调度移动的传感器，我们提供了基于样本的调度器作为中间件来建模应用程序调用和传感器真实的活动之间的动态数学关系。因此，调度器能够在用户执行的各种应用上下文下动态地配置传感器刷新速率。我们评估这个框架与广泛的移动的应用程序。实验结果表明，与传统的耗尽检测操作相比，新的低功耗调度器在中间件上花费了97 ms的响应延迟作为开销，减少了70%的传感器能耗.
Current smartphones are very rich in the type of sensors to provide various user-behavior tracing and social network sharing, ie, pervasive social networking applications. Sensor power consumption contributes a significant part of overall power budget in system since each mobile application always actives the related sensors without any restriction. Even worse, in-smartphone sensors are usually activated with full frequencies to match the flushing rates of a group of aggregated tasks, known as full polling-based detection, which results in significant unnecessary activities on sensors and fast battery sucking-up. In this work, we propose a low-power sensor polling strategy for mobile applications to dynamically remove unnecessary sensor activities. With this design, the unrelated sensors can keep in sleeping status for longer time. To schedule mobile sensors, we provide sample-based scheduler as a middleware to model the on-the-fly mathematical relationship between application invoking and sensor real activities. Thus, the scheduler is able to dynamically configure sensor flushing rates under various application context that isexecuted by users. We evaluate this framework with a wide range of mobile applications. The results show that our new low-power scheduler spends a tiny responding delay (97 ms) in the middleware, as the overhead, to reduce 70% sensor energy consumption, comparing with the conventional exhausting detecting operation.
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DOI：
10.1109/iccitechnology.2013.6579514
发表时间：
2013-06
期刊：
2013 Third International Conference on Communications and Information Technology (ICCIT)
影响因子：
--
作者：
S. Taleb;Nadine Abbas;Hazem M. Hajj;Z. Dawy
通讯作者：
S. Taleb;Nadine Abbas;Hazem M. Hajj;Z. Dawy
DOI：
10.1109/mdm.2011.76
发表时间：
2011-06
期刊：
2011 IEEE 12th International Conference on Mobile Data Management
影响因子：
--
作者：
Archan Misra;Lipyeow Lim
通讯作者：
Archan Misra;Lipyeow Lim
DOI：
10.1145/2070942.2070969
发表时间：
2011-11
期刊：
--
影响因子：
--
作者：
Taiwoo Park;Jinwon Lee;Inseok Hwang;Chungkuk Yoo;L. Nachman;Junehwa Song
通讯作者：
Taiwoo Park;Jinwon Lee;Inseok Hwang;Chungkuk Yoo;L. Nachman;Junehwa Song
DOI：
10.1109/iswcs.2010.5624490
发表时间：
2010-11
期刊：
2010 7th International Symposium on Wireless Communication Systems
影响因子：
--
作者：
Sian Lun Lau;I. König;K. David;Baback Parandian;Christine Carius-Düssel;Martin Schultz
通讯作者：
Sian Lun Lau;I. König;K. David;Baback Parandian;Christine Carius-Düssel;Martin Schultz
影响因子：
4.3
作者：
Y. Uhm;I. Hong;Gwanyeon Kim;Byoungjoo Lee;Sehyun Park
通讯作者：
Y. Uhm;I. Hong;Gwanyeon Kim;Byoungjoo Lee;Sehyun Park