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A Case for Atmospheric Transmittance: Solar Energy Prediction in Wireless Sensor Nodes
(2018)2018 IEEE International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData)In this paper, we propose four novel schemes for solar energy prediction in wireless sensor nodes. Two of the schemes (WCMA-T and ProEnergy-T) are extensions of stateof-the-art schemes, while the remaining schemes (EWMA-T and Delta-T) are new. The proposed strategies leverage the extraterrestrial solar model [5] to get better prediction accuracy compared to state-of-the-art. We restrict our scope to schemes that only employ local information. ...Conference Paper -
End-to-end Real-time Guarantees in Wireless Cyber-physical Systems
(2016)Proceedings 2016 IEEE Real-Time Systems Symposium. RTSS 2016Conference Paper -
Self-Sustainability in Nano Unmanned Aerial Vehicles: A Blimp Case Study
(2017)Proceedings of the Computing Frontiers Conference (CF'17)Conference Paper -
FlockLab 2: Multi-Modal Testing and Validation for Wireless IoT
(2020)The development, evaluation, and comparison of wireless IoT and cyber-physical systems requires testbeds supporting inspection of logical states and accurate observations of physical performance metrics. We present FlockLab~2, a second generation testbed supporting multi-modal, high-accuracy and high-dynamic range measurements of power and logic timing and at the same time in-situ debug and trace infrastructure of modern microcontrollers ...Conference Paper -
Injecting Descriptive Meta-Information into Pre-Trained Language Models with Hypernetworks
(2021)Proceedings of Interspeech 2021There is a growing trend to deploy deep neural networks at the edge for high-accuracy, real-time data mining and user interaction. Applications such as speech recognition and language understanding often apply a deep neural network to encode an input sequence and then use a decoder to generate the output sequence. A promising technique to accelerate these applications on resource-constrained devices is network pruning, which compresses ...Conference Paper -
Torpor: A Power-Aware HW Scheduler for Energy Harvesting IoT SoCs
(2018)2018 28th International Symposium on Power and Timing Modeling, Optimization and Simulation (PATMOS)Conference Paper -
Wearable, Energy-Opportunistic Vision Sensing for Walking Speed Estimation
(2017)2017 IEEE Sensors Applications Symposium (SAS)Conference Paper -
Optimal Power Management for Energy Harvesting Systems with A Backup Power Source
(2021)2021 10th Mediterranean Conference on Embedded Computing (MECO)Energy harvesting has been extensively used to allow for long-term and unattended operation of nodes in large-scale distributed systems. However, the smaller the relative rechargeable energy storage of the harvesting system, the higher is the sensitivity of its operation to short-term non-deterministic changes of the harvested power or the current power demand. A reliable and predictable node operation can be achieved with an additional ...Conference Paper -
Deep Partial Updating: Towards Communication Efficient Updating for On-device Inference
(2022)Lecture Notes in Computer Science ~ Computer Vision – ECCV 2022Emerging edge intelligence applications require the server to retrain and update deep neural networks deployed on remote edge nodes to leverage newly collected data samples. Unfortunately, it may be impossible in practice to continuously send fully updated weights to these edge nodes due to the highly constrained communication resource. In this paper, we propose the weight-wise deep partial updating paradigm, which smartly selects a small ...Conference Paper -
Using system context information to complement weakly labeled data
(2021)arXiv ~ Proceedings of the First Workshop on Weakly Supervised Learning (WeaSuL), May 7, 2021, co-located with ICLR (Online)Conference Paper