Vincent Lannurien
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117 lines
4.4 KiB
Markdown
117 lines
4.4 KiB
Markdown
---
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title: MobiSys 2024 Digest
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venue: MobiSys
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year: 2024
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date: '2024-01-01'
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tags: []
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paper_count: 13
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draft: false
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---
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13 papers selected.
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### WAIS: Leveraging WiFi for Resource-Efficient SLAM
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*Aditya Arun 0002, William Hunter, Roshan Sai Ayyalasomayajula, Dinesh Bharadia*
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**TL;DR** — Demonstrates that commodity WiFi signals can replace LiDAR for simultaneous localization and mapping, dramatically cutting the resource cost of robot/AR navigation.
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### UWB-Fi: Pushing Wi-Fi towards Ultra-wideband for Fine-Granularity Sensing
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*Xin Li 0070, Hongbo Wang, Zhe Chen 0015, Zhiping Jiang *et al.**
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**TL;DR** — Extends standard Wi-Fi to UWB-class sensing resolution without hardware changes, enabling centimeter-level gesture and motion detection on existing infrastructure.
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### Radarize: Enhancing Radar SLAM with Generalizable Doppler-Based Odometry
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*Emerson Sie, Xinyu Wu, Heyu Guo, Deepak Vasisht*
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**TL;DR** — Introduces a Doppler-derived odometry method that generalizes radar-based SLAM across environments and radar hardware without per-deployment retraining.
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### ChirpTransformer: Versatile LoRa Encoding for Low-power Wide-area IoT
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*Chenning Li, Yidong Ren, Shuai Tong, Shakhrul Iman Siam *et al.**
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**TL;DR** — Redesigns LoRa chirp encoding with a transformer-based scheme that simultaneously improves throughput, range, and coexistence for large-scale IoT deployments.
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### Willow: Practical WiFi Backscatter Localization with Parallel Tags
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*Jinyan Jiang, Jiliang Wang, Yijie Chen, Shuai Tong *et al.**
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**TL;DR** — Enables concurrent localization of multiple passive backscatter tags over commodity WiFi, making large-scale battery-free asset tracking practical.
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### Pantheon: Preemptible Multi-DNN Inference on Mobile Edge GPUs
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*Lixiang Han, Zimu Zhou, Zhenjiang Li*
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**TL;DR** — Provides a preemptible scheduling runtime for concurrent DNN workloads on edge GPUs, achieving low-latency inference without sacrificing throughput under mixed real-time demands.
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### ARISE: High-Capacity AR Offloading Inference Serving via Proactive Scheduling
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*Z. Jonny Kong, Qiang Xu 0006, Y. Charlie Hu*
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**TL;DR** — Proactively schedules AR inference offloading by predicting gaze and scene dynamics, significantly increasing server capacity while meeting strict latency budgets.
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### CACTUS: Dynamically Switchable Context-aware micro-Classifiers for Efficient IoT Inference
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*Mohammad Mehdi Rastikerdar, Jin Huang, Shiwei Fang, Hui Guan 0001 *et al.**
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**TL;DR** — Deploys a family of tiny context-aware classifiers on microcontrollers that switch at runtime to match workload context, cutting energy by orders of magnitude versus monolithic models.
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### Empowering In-Browser Deep Learning Inference on Edge Through Just-In-Time Kernel Optimization
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*Fucheng Jia, Shiqi Jiang 0002, Ting Cao 0003, Wei Cui *et al.**
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**TL;DR** — Uses JIT kernel specialization to close the performance gap between browser-based and native DNN inference on edge devices, enabling high-throughput on-device AI in web apps.
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### FedConv: A Learning-on-Model Paradigm for Heterogeneous Federated Clients
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*Leming Shen, Qiang Yang 0018, Kaiyan Cui, Yuanqing Zheng *et al.**
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**TL;DR** — Proposes learning directly over model parameters rather than data, allowing federated learning to work across radically heterogeneous IoT devices without sharing raw data or requiring uniform architectures.
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### SoilCares: Towards Low-cost Soil Macronutrients and Moisture Monitoring Using RF-VNIR Sensing
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*Juexing Wang, Yuda Feng, Gouree Kumbhar, Guangjing Wang 0001 *et al.**
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**TL;DR** — Combines RF and near-infrared sensing in a low-cost handheld device to measure soil nutrients and moisture, demonstrating real agricultural field deployments.
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### MobiAir: Unleashing Sensor Mobility for City-scale and Fine-grained Air-Quality Monitoring with AirBERT
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*Yuxuan Liu 0010, Haoyang Wang 0012, Fanhang Man, Jingao Xu *et al.**
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**TL;DR** — Leverages mobile sensors on vehicles and pedestrians with a BERT-style spatio-temporal model to achieve city-scale, fine-grained air quality maps at a fraction of the cost of static sensor networks.
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### Joey: Supporting Kangaroo Mother Care with Computational Fabrics
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*Qijia Shao, Jiting Liu, Emily Bejerano, Ho-Man Colman Leung *et al.**
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**TL;DR** — Embeds soft physiological sensors directly into a wearable fabric wrap to monitor premature infants during skin-to-skin care, demonstrating a compelling real-world clinical deployment.
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