Spreading Factor Allocation and Rate Adaption for Minimizing Age of Information in LoRaWAN

LoRaWAN has been widely deployed to support long-range connections for Internet of Things (IoT). However, due to frequent collisions, packet delivery performance in LoRaWAN has become a concern. Age of information (AoI) is used to measure information freshness, which refers to the elapsed time from when the information was first generated. For time-sensitive IoT applications, such as fire alarm, information freshness plays an important role. In this paper, we investigate the AoI model for packet sending and collision in LoRaWAN. To the best of our knowledge, this is the first attempt to improve LoRaWAN from the perspective of AoI. We then propose two efficient methods to minimize the AoI in LoRaWAN. Finally, our experiments show that the proposed methods can achieve the lowest AoI and the packet delivery ratio (PDR) is also improved by 52.14% on average compared with the default ADR scheme in LoRaWAN.

[1]  Rida El Chall,et al.  Adaptive algorithm for spreading factor selection in LoRaWAN networks with multiple gateways , 2020, Comput. Networks.

[2]  Yinghui Li,et al.  DyLoRa: Towards Energy Efficient Dynamic LoRa Transmission Control , 2020, IEEE INFOCOM 2020 - IEEE Conference on Computer Communications.

[3]  Bin Wang,et al.  Characterizing Packet Loss in City-Scale LoRaWAN Deployment: Analysis and Implications , 2020, 2020 IFIP Networking Conference (Networking).

[4]  Wisam Farjow,et al.  Optimization of Spreading Factor Distribution in High Density LoRa Networks , 2020, 2020 IEEE 91st Vehicular Technology Conference (VTC2020-Spring).

[5]  Walid Saad,et al.  Optimized Age of Information Tail for Ultra-Reliable Low-Latency Communications in Vehicular Networks , 2019, IEEE Transactions on Communications.

[6]  Matthew O. Adigun,et al.  LoRa Gateway Placement at the University of Zululand: A Case Study , 2019, 2019 International Conference on Smart Applications, Communications and Networking (SmartNets).

[7]  Hirley Alves,et al.  K-Means Spreading Factor Allocation for Large-Scale LoRa Networks , 2019, Sensors.

[8]  Eytan Modiano,et al.  Optimizing age of information in wireless networks with perfect channel state information , 2018, 2018 16th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt).

[9]  Eytan Modiano,et al.  Scheduling Policies for Minimizing Age of Information in Broadcast Wireless Networks , 2018, IEEE/ACM Transactions on Networking.

[10]  E. Modiano,et al.  Scheduling Algorithms for Minimizing Age of Information in Wireless Broadcast Networks with Random Arrivals , 2017, IEEE Transactions on Mobile Computing.

[11]  Francesca Cuomo,et al.  EXPLoRa: Extending the performance of LoRa by suitable spreading factor allocations , 2017, 2017 IEEE 13th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob).

[12]  Utz Roedig,et al.  Do LoRa Low-Power Wide-Area Networks Scale? , 2016, MSWiM.

[13]  Sanjit Krishnan Kaul,et al.  Minimizing age of information in vehicular networks , 2011, 2011 8th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks.

[14]  Sheldon M. Ross,et al.  Stochastic Processes , 2018, Gauge Integral Structures for Stochastic Calculus and Quantum Electrodynamics.

[15]  M. Hata,et al.  Empirical formula for propagation loss in land mobile radio services , 1980, IEEE Transactions on Vehicular Technology.