Data aggregation schemes for Machine-to-Machine gateways: Interplay with MAC protocols
Data aggregation schemes for Machine-to-Machine gateways: Interplay with MAC protocols
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发表时间：
2012-07
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通讯作者：
J. Matamoros;C. Antón-Haro
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作者：
J. Matamoros;C. Antón-Haro
本文主要研究毛细M2M(Machine-to-Machine)网络在空间随机场估计中的应用。毛细网络由M2M网关协调，该M2M网关负责(I)收集空间相关的传感器观测集合；以及(Ii)在将这些观测重新传输到远程应用服务器之前聚集(压缩)这些观测。我们考虑了一个现实场景，其中基于竞争的媒体访问控制方案用于传感器到GW的通信。在这种情况下，我们试图确定两个传输阶段的最佳持续时间，即传感器到网关和网关到应用服务器，以达到在分组冲突和压缩水平方面的最佳折衷。通过这样做，可以最小化重建随机场中的失真。我们还研究了特定的数据聚合方案是如何影响最优工作点的，这两种方案都是基于卡尔胡宁-洛伊̀Ve变换或底层场的空间相关性属性。
This paper focuses on the use capillary M2M (Machine-to-Machine) networks for the estimation of spatial random fields. The capillary network is coordinated by an M2M gateway which is in charge of (i) collecting the set of spatially correlated sensor observations; and (ii) aggregating (compressing) such observations prior to their re-transmission to a remote application server. We consider a realistic scenario where a contention-based Medium Access Control scheme is used for sensor-to-GW communications. In this context, we attempt to determine the optimal duration of the two transmission phases, namely, sensor-to-gateway and gateway-to-application server, in such a way that the best trade-off in terms of packet collisions and compression level is attained. By doing so, the distortion in the reconstructed random field can be minimized. We also investigate how the optimal operating point is affected by the specific data aggregation scheme, both of them being based on the Karhunen-Loève transform, or the spatial correlation properties of the underlying field.