SCENTS: Collaborative Sensing in Proximity IoT Networks
SCENTS: Collaborative Sensing in Proximity IoT Networks
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DOI：
10.1109/percomw.2019.8730863
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发表时间：
2019-03
期刊：
影响因子：
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通讯作者：
Chenguang Liu;Jie Hua;C. Julien
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文献类型：
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作者：
Chenguang Liu;Jie Hua;C. Julien
移动应用程序通常使用设备上的传感器来持续提供上下文：温度、位置、声音等。通过协作感知上下文，设备可以节省能源并共享稀有功能，同时在感测质量方面做出最小的权衡。此外，通过利用已经活跃的通信行为，可以以非常低的成本收集环境上下文信息。我们提出了一个通用的协作感知框架 SCENTS，以支持移动物联网应用的集体感知。 SCENTS 利用了物联网网络的两个事实：(1) 设备持续参与低级设备发现机制，(2) 附近的设备往往对许多环境上下文属性具有相似的值。我们证明 SCENTS 平衡了感知实现和跨设备能源消耗的公平性。我们使用真实的物联网设备和真实世界的智慧城市场景来衡量 SCENTS 的性能。
Mobile applications commonly use on-device sensors to continuously provide context: temperature, position, sound, etc. By collaborating to sense context, devices can save energy and share rare capabilities with minimal tradeoffs in sensing quality. Further, by leveraging already active communication behaviors, ambient context information can be collected at very little cost. We present a generic collaborative sensing framework, SCENTS, to support collective sensing for mobile IoT applications. SCENTS leverages two truths about IoT networks: (1) devices participate continuously in low-level device discovery mechanisms and (2) nearby devices tend to have similar values for many ambient context properties. We show that SCENTS balances sensing fulfillment and the fairness of energy consumption across devices. We measure the performance of SCENTS using real IoT devices and real world smart-city scenarios.