An Efficient Equal Air-Time Transmission Strategy for Wireless Seismometer Array Based on LoRaWAN With CuckooHash

Abstract

Recently, large-scale wireless seismometer array (WSA) have played an increasingly important role in oil/gas exploration industry and seismology research. However, due to limited wireless channel bandwidth, transmission latency and high power consumption caused by transmission conflicts in battery-powered seismometers, real-time large-scale WSA system remains unsolved. In this article, we introduce a LoRaWAN-based WSA system with high precise time slot deriving from a synchronization platform composed of GPS timing module and temperature compensated crystal oscillator (TCXO) clock counter. Using the global sharing time slot, we propose an Equal Air Time and CuckooHash (EAT&CH) algorithm for the WSA to resolve channel congestion and delays when multiple seismometers upload data simultaneously. In EAT&CH, an equal air-time spreading factor (SF) allocation method based on the coarse/fine-grained theory is employed to reduce the collision probability of data transmission. To improve the scalability of the WSA in terms of reducing both collision probability and data delay, a different carrier frequency (CF) channel with the same SF allocation plan depending on CuckooHash is designed to reduce the network latency. Simulation results show that the proposed algorithm achieves nearly 100% data extraction rate of the WSA with less than two times the delay, compared with the existing Adaptive Data Rate (ADR) mechanism.