p-CARMA: Politely Scaling LoRaWAN
p-CARMA: Politely Scaling LoRaWAN
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DOI：
10.5555/3400306.3400310
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发表时间：
2020-02
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影响因子：
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通讯作者：
N. Kouvelas;V. Rao;R. V. Prasad;G. Tawde;K. Langendoen
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作者：
N. Kouvelas;V. Rao;R. V. Prasad;G. Tawde;K. Langendoen
远程广域网 (LoRaWAN) 满足了能源受限的物联网设备对运行寿命和以最佳方式扩展通信范围的需求。然而，LoRaWAN 的极简设计无法处理来自超过数百个设备连接到单个网关的密集部署的流量，因为每个 LoRa 设备传输数据包时没有任何有关介质可用性的信息。在本文中，我们尝试通过多种方式提高 LoRaWAN 的可扩展性，为每个网关提供数千个设备服务。我们提出了一种名为 p 持久信道活动识别多路访问 (p-CARMA) 的新颖协议，该协议利用 LoRaWAN 的信道活动检测 (CAD) 作为评估信道是否空闲的粗略机制。由于 CAD 的缺陷（它只扫描前导码，而不扫描任何通道活动），p-CARMA 以概率方式运行，每个设备根据本地估计决定 p 值。在运行之初，该估计来自纯本地信息，即没有网关的参与，设备自动适应环境的变化。然后，有关累积设备延迟的关键信息将协助 p 值的调整，这些信息由网关以定期、大的时间跨度进行多播。为了评估 p-CARMA 的性能，我们根据 LoRaWAN CAD 机制的详细特征（涉及大量实际实验）在 ns-3 中实现了它。我们将 p-CARMA 与普通 LoRaWAN 以及使用理论上最佳 p = 1=N（N 是设备总数）的变体进行了比较。仿真结果表明，在处理数千个设备时，p-CARMA 的数据包接收率比 LoRaWAN 高出三倍至二十倍。此外，在扩大规模时，其适应性比固定 p 值高出 5.25 倍。此外，与普通 LoRaWAN 相比，p-CARMA 的每台设备平均能耗减少了 37.31%-58.17%。
Long Range Wide Area Network (LoRaWAN) covers the needs of energy-constrained IoT-devices for operational longevity and extended communication range in a best-effort fashion. However, Lo- RaWAN’s minimalist design cannot handle the traffic from dense deployments with more than a few hundred devices connected to a single gateway, since each LoRa-device transmits data-packets without any information regarding the availability of the medium. In this paper, we try to improve the scalability of LoRaWAN by manifolds, serving thousands of devices per gateway. We present a novel protocol called p persistent-Channel Activity Recognition Multiple Access (p-CARMA) that exploits LoRaWAN’s Channel Activity Detection (CAD) as a crude mechanism to assess if the channel is free. Due to CAD’s imperfections (it only scans for preambles, not for any channel activity) p-CARMA operates probabilistically with each device deciding on a p value based upon local estimation. At the beginning of operation, this estimate is derived from pure local information, that is without involvement of the gateway, and devices automatically adapt to changes in the environment. Then, the adaptation of p-value is assisted by critical information on the cumulative device-delays, multicasted by the gateway at regular, large timespans. To evaluate the performance of p-CARMA, we implemented it in ns-3 based upon a detailed characterization of LoRaWAN’s CAD mechanism involving an extensive set of real-world experiments. We compared p-CARMA to vanilla LoRaWAN as well as a variant using the theoretically optimal p = 1=N (N being the total number of devices). The simulation results show that p-CARMA achieves from three-fold, up to a twenty-fold higher Packet Reception Ratio than LoRaWAN while handling thousands of devices. Further, its adaptivity outperforms the fixed p-value by a factor of 5.25 when scaling up. Moreover, p-CARMA does so while consuming 37.31%-58.17% less energy on average per device compared to vanilla LoRaWAN.