A lightweight decision system that dynamically determines when to transmit by checking short-term trends in signal strength, while using Non-volatile Memory (NVM) to retain packets in unfavorable channel conditions and across energy failures is designed.
Abstract
We enable backscatter communication in the battery-less mobile Internet of Things (IoT). Backscatter communication is extensively studied in static settings. Existing designs are, however, fundamentally mismatched with mobility and time-varying energy patterns. Channel conditions rapidly fluctuate, impacting the achievable data rates and thus transmission costs. Energy availability varies unpredictably, possibly forcing devices to remain quiescent to recharge energy buffers. The two issues compound each other: while recharging, a battery-less mobile IoT device may miss more favorable channel conditions. We design a lightweight decision system that dynamically determines when to transmit by checking short-term trends in signal strength, while using Non-volatile Memory (NVM) to retain packets in unfavorable channel conditions and across energy failures. Using a prototype we built and real-world mobility and power traces, we compare our design against a rate-adaptive baseline that only considers the instantaneous channel conditions. Experimental results show that our system improves throughput by up to 5.16x while reducing transmission energy consumption by up to 47.3%, with only 0.23% - 7.3% additional energy overhead.
WiFi backscatter has emerged as a promising technology for green Internet of Things (IoT) connectivity by enabling battery-free devices to communicate through widely available WiFi signals. Despite substantial progress in recent years, a considerable gap remains between research prototypes and practical deployment. Thi...
This paper derives the energy model for single-node communication and extends it to multiple-sensor-node communication where several sensors concurrently transmit their information and derives an energy model for a battery-free sensor node that relies on the energy harvested from ambient sources to drive its operation.
Siaka Konaté, Changli Li, Drissa Traoré et al.· Computer Networks and Commun...· 0 citations
The growing adoption of Internet of Things (IoT) applications has increased the demand for resilient and scalable wireless networks, especially in environments where wired infrastructure is limited. This work presents the experimental evaluation of a Wi-Fi mesh network based on the ESP32-C6 microcontroller and the ESP-...
Graziele de Cássia Rodrigues, Marcelo Moreira Tiago, Theo Lins et al.· 2026 10th International Symp...· 0 citations
Past decades have witnessed the rapid development of battery-free backscatter-based cameras, opening up promising long-term and sustainable surveillance applications by harvesting wireless energy. However, limited by the fluctuations of the ambient energy, existing backscatter systems suffer from unreliability issues,...
Hui-Xin Dong, Xin-Yi Wu, Liu Yang et al.· ACM Transactions on Internet...· 0 citations
Low Power Wide Area Networks (LPWANs) such as LoRa commonly adopt unslotted ALOHA for its simplicity, but the resulting throughput ceiling (0.183 frames/frame-time) limits scalability. We propose a heterogeneous multi-channel collision resolution system that partitions $M$ channels into contention channels and dedicate...
Song Fan, Zhi Dou, Jun-Bae Seo et al.· IEEE Transactions on Communi...· 0 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.