同步大规模IoT网络中的数据聚合：粒度、可靠性和延迟权衡
Data Aggregation in Synchronous Large-scale IoT Networks: Granularity, Reliability, and Delay Tradeoffs
摘要：
本文研究了大规模定期部署的物联网（IoT）网络中的数据聚合，其中设备生成同步的时间触发流量（例如，测量或更新）。数据粒度，在信息内容和时间分辨率方面，由所生成的数据包的大小和数据包生成的占空比来参数化。设备上生成的数据包通过静态地面网关聚合。在所有网关中采用通用频率重用，并将随机调度用于与每个网关相关联的IoT设备。这种网络模型在环境传感、精准农业和地质地震传感等方面有应用。为此，我们开发了一种新的时空数学模型来表征数据粒度，传输可靠性和延迟之间的相互作用。开发的模型考虑了几个物联网设计参数，包括数据包大小、生成占空比、设备和网关空间密度、传输速率自适应、功率控制和天线方向性。为了便于分析，我们提出了两个准确的近似，泊松点过程的基础上，来表征信号干扰噪声比（SINR）的传输可靠性。对于延迟分析，我们提出了一个相位类型的到达/离开（PH/PH/1）排队模型，占数据包生成，传输调度，和速率敏感的SINR为基础的数据包离开。所开发的模型用于获得IoT设备的最佳传输速率，以最大限度地减少延迟。数值结果描绘了数据聚合的数据包大小和到达间隔时间的联合可行性范围，并揭示了部署定向天线时的显着收益。
英文摘要：
This paper studies data aggregation in large-scale regularly deployed Internet of Things (IoT) networks, where devices generate synchronized time-triggered traffic (e.g., measurements or updates). The data granularity, in terms of information content and temporal resolution, is parameterized by the sizes of the generated packets and the duty cycle of packet generation. The generated data packets at the devices are aggregated through static terrestrial gateways. Universal frequency reuse is adopted across all gateways and randomized scheduling is utilized for the IoT devices associated with each gateway. Such network model finds applications in environmental sensing, precision agriculture, and geological seismic sensing to name a few. To this end, we develop a novel spatiotemporal mathematical model to characterize the interplay between data granularity, transmission reliability, and delay. The developed model accounts for several IoT design parameters, which include packet sizes, generation duty cycle, devices and gateways spatial densities, transmission rate adaptation, power control, and antenna directivity. For tractable analysis, we propose two accurate approximations, based on the Poisson point process, to characterize the signal-to-interference-plus-noise-ratio (SINR) based transmission reliability. For the delay analysis, we propose a phase-type arrival/departure (PH/PH/1) queueing model that accounts for packet generation, transmission scheduling, and rate-sensitive SINR-based packet departure. The developed model is utilized to obtain the optimal transmission rate for the IoT devices that minimizes delay. The numerical results delineate the joint feasibility range of packet sizes and inter-arrival times for data aggregation and reveal significant gains when deploying directional antennas.
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