Revealing insights for improvements in LoRaWAN in multiple applications scenarios: Poster abstract
We study LoRaWAN's performance when multiple applications are concurrently running over the same LoRaWAN network. We consider applications that generate data packets using a Poisson process, a random distribution, and at periodic intervals. The LoRa PHY layer supports a number of communication settings. However, here we focus on two specific settings: the setting recommended by LoRaWAN and the setting that yields the highest possible data rate in LoRa. Our results demonstrate the following: (i) LoRaWAN favours applications that generate packets at a higher periodic rate, (ii) LoRAWAN does not favour applications that generate packets at a higher rate under Poisson and uniform random distribution, (iii) LoRaWAN's recommended PHY setting demonstrates poor performance, (iv) LoRa's fastest data rate setting outperforms the LoRaWAN recommended setting, and (v) LoRaWAN favours applications that generate packets using uniform random and Poisson distributions over application that generates packet at periodic interval. Our results also hint that using multi-hop communication along with the LoRa's fastest data rate setting can not only increase the setting's coverage, but it may still deliver better performance relative to the LoRaWAN's recommended setting.
|Conference||17th ACM Conference on Embedded Networked Sensor Systems, SenSys 2019|
Farooq, M.O. (Muhammad Omer), & Kunz, T. (2019). Revealing insights for improvements in LoRaWAN in multiple applications scenarios: Poster abstract. In SenSys 2019 - Proceedings of the 17th Conference on Embedded Networked Sensor Systems (pp. 434–435). doi:10.1145/3356250.3361956