Technology Category
Planning, Routing, and Scheduling: Optimization of Spatio-temporal SystemsReasoning under Uncertainty: Stochastic OptimizationConstraint Satisfaction and Optimization: Distributed CSP/Optimization
Time-Constrained Erasure Correction for Data Recovery in UAV-LoRa-WuR Networks
🤖 AI Summary
To address the challenge of reliable sensor data recovery under high packet loss, stringent latency constraints, and limited energy in UAV-assisted LoRa networks integrated with wake-up radio (WuR), this paper proposes a latency-sensitive erasure coding decision framework. Methodologically, we formulate a joint optimization model incorporating sensor energy budgets, UAV hovering time, and ground node density; design two adaptive erasure correction schemes—based on Reed–Solomon and related codes—under latency constraints; and integrate probabilistic packet-loss modeling with joint latency-energy analysis. Our key contribution is the first establishment of coding activation criteria and code-selection guidelines specifically for UAV-LoRa-WuR scenarios. Experimental results demonstrate that, with moderate redundancy, the proposed coding strategy significantly improves data recovery rates over uncoded transmission. Moreover, the analytical framework provides interpretable and quantifiable coding decisions for practical deployment.
Technology Category
Application Category
📝 Abstract
We described two erasure-correction schemes for data recovery in UAV-LoRa-WuR networks. Our results show that unless the maximum number for redundant frames a sensor can send per data-collection cycle is very small, erasure coding provides noticeable improvements over an uncoded transmissions. Whether to employ coding -- and if so, which type -- should be determined based on the sensors' energy budget (which dictates the maximum redundancy), the UAV's hovering time, and the node density. The analytical framework presented above aids in this decision making.
Problem
Research questions and friction points this paper is trying to address.
Erasure-correction schemes for UAV-LoRa-WuR data recovery
Optimizing redundancy based on energy and hovering constraints
Framework for choosing coding type in sensor networks
Innovation
Methods, ideas, or system contributions that make the work stand out.
Erasure-correction schemes for UAV-LoRa-WuR networks
Erasure coding improves uncoded transmissions significantly
Decision framework based on energy, hovering time, density
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