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Late breaking results: adaptive ensembles of dynamic DNNs for collaborative edge inference

Title: Late breaking results: adaptive ensembles of dynamic DNNs for collaborative edge inference
Authors: Hu, Mingyu; Singh, Amit Kumar; Hare, Jonathon; Merrett, Geoff
Publisher Information: IEEE
Publication Year: 2026
Collection: University of Southampton: e-Prints Soton
Description: Edge computing enables low-latency and privacy-preserving DNN inference, yet heterogeneous and dynamically changing device resources make it difficult to satisfy real-time constraints. In this paper, we present AdaEnsemble, an adaptive and collaborative ensemble inference framework that integrates Dynamic DNNs with deadline-aware scheduling. The system profiles accuracy and latency offline and selects both model widths and participating devices at runtime to maximize accuracy under a given deadline. Experiments on heterogeneous edge devices show that AdaEnsemble adapts effectively to different latency requirements and consistently outperforms the state-of-art.
Document Type: conference object
File Description: text
Language: English
Relation: https://eprints.soton.ac.uk/509859/1/DATE2026_LBR_AdaEnsemble_Mingyu.pdf; Hu, Mingyu, Singh, Amit Kumar, Hare, Jonathon and Merrett, Geoff (2026) Late breaking results: adaptive ensembles of dynamic DNNs for collaborative edge inference. In Design, Automation and Test in Europe Conference 2026. IEEE. 3 pp . (In Press)
Availability: https://eprints.soton.ac.uk/509859/; https://eprints.soton.ac.uk/509859/1/DATE2026_LBR_AdaEnsemble_Mingyu.pdf
Rights: cc_by_4
Accession Number: edsbas.EC42562A
Database: BASE