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edge computing

2,571 papers

#edge computing Book Open access Sep 2026

QMScaler: A QoS-Constrained Resource-Efficient Microservice Autoscaling Framework for Edge Environments

QMScaler is proposed, a QoS-driven microservice horizontal scaling framework based on Monte Carlo Tree Search (MCTS) that aims to minimize the number of container instances while meeting the QoS requirements of multiple application functions.

Tianyang Zheng, Pengfei Yang, Zhe Xu et al. · 0 citations
#edge computing Book Open access Sep 2026

Sparsity-aware Fine-Grained Parallelization for Set Intersection Computations in Graph Datasets

A fine-grained GPU parallelization approach that adapts to workload characteristics by assigning set intersection computations within a graph to the most suitable parallelization strategies, and predicts the optimal parallelization approach between this fine-grained and other state-of-the-art GPU kernels with 88% accur...

Atharva Gondhalekar, Wu-Chun Feng · 0 citations
#edge computing Book Open access Sep 2026

Chapel for Parallel AND Distributed GPU Computing: A Case Study with Jaccard Similarity

Overall, when evaluating both Chapel and MPI+X implementations of partitioned Jaccard similarity on up to 16 A100-80GB GPUs across four nodes, Chapel achieves comparable performance to MPI+X while also delivering significantly better programmer productivity and agility.

Paul Sathre, Wu-Chun Feng · 0 citations
#edge computing Book Open access Sep 2026

A Neuromorphic Dual-Stage Swin Transformer for Wetland Classification on Edge Platforms

The Dual-Stage Spiking Swin Transformer (D2S-SwinT), a neuromorphic architecture that integrates the feature representation capability of Swin Transformers with the event-driven efficiency of brain-inspired computation, is proposed, a neuromorphic architecture that integrates the feature representation capability of Sw...

Hong-Jiang Deng, Wen-Hua Hu, Hao-Hui Peng et al. · 0 citations
#edge computing Book Open access Sep 2026

Vadar: Runtime Performance Variance Detection and Diagnosis for Parallel Applications

Vadar adopts a non-intrusive dynamic interception mechanism to monitor parallel applications with state transition detection to cope with workload change at runtime, and provides comprehensive monitoring for both regular and irregular computational workloads.

Yi-Fan Jia, Shuang Niu, Yu-Hang Hu et al. · 0 citations
#edge computing Open access Sep 2026

Cloud-Edge collaborative adaptive dual-graph spatio-temporal passenger flow forecasting model for smart high-speed railway services

Passenger flow in rapidly developing high-speed railway networks varies with temporal fluctuations, spatial interactions among stations, and regional travel dependencies. Accurate forecasts support the management of station operations, resource allocation, and service optimization, yet methods that impose fixed spatial...

Ling Liu, Majid Ghani Varzaneh · 0 citations
#edge computing Open access Sep 2026

Semantic Edge Orchestration for 6G-Enabled Immersive Media Broadcasting

The rapid evolution of 6G networks is expected to transform immersive media broadcasting by enabling ultra-low-latency communication, intelligent edge computing, and high-capacity transmission for extended reality, holographic content, and interactive multimedia. However, conventional edge resource management remains l...

Lunatari Sanbella, Chandra Lukita, Anandha Fitriani et al. · 0 citations
#edge computing Open access Sep 2026

Statistical Rigor in YOLO Model Evaluation: Bootstrap Confidence Intervals and Failure Mode Analysis

The reliance on single-point metric estimates (such as a solitary mAP score) to benchmark object detection models frequently masks underlying sample variances, leading to overconfident deployment decisions. This paper presents an automated post-training validation pipeline for YOLO models designed to enforce statistica...

William Steve Rodriguez Villamizar · 0 citations
#edge computing Dataset Open access Sep 2026

LUCYD-PISCO training-set sources v5: in-focus plankton object library and object-free PISCO background textures

LUCYD-PISCO training-set sources (v5) Source data needed to regenerate the synthetic training set used to retrain the LUCYD deconvolution network for PISCO (Plankton In Situ Camera Observation) extended-depth-of-field (TAG-lens) images. Code: https://git.geomar.de/team-optics/plankton/underwater-lucyd (sim/gen_trainset...

Veit Dausmann · 0 citations
#edge computing Dataset Open access Sep 2026

Mirror, Mirror, in XR: Asymmetric Mimicry in XR Social Interactions

Mirror, Mirror, in XR: Motion-Capture Dataset, Processing Pipeline, and Analysis Code Description This deposit contains the full data-processing and analysis pipeline underlying a within-subjects VR study of imposed social mirroring. Twelve dyads (24 participants) held structured conversations under three counterbalanc...

Anonymous · 0 citations
#edge computing Dataset Open access Sep 2026

Data, figures and code for: A single oscillator response sets the exponents of synchronization transitions

Changes in v1.0.7. Two faults in the cavity figure, both found on the page. The near lower corner of the box at the far end was missing, and with it about a sixth of the front lower edge. The two panels of that figure are each wider and taller than the drawing they hold, which is what lets a long flat cavity and a cone...

Tanvir Mahmud Mahim, M. Mosaddequr Rahman, Abu S. M. Mohsin · 0 citations

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Microsoft Research Blog Oct 6, 2026

What AI gets wrong and what failure teaches us

Jennifer Neville did not want to go into computer science—but that’s exactly where she landed. Neville discusses the starts and stops that led to her professional sweet spot and her work identifying “surprising failures” making it hard for AI to handle complexity.  The post What AI gets wrong and what failure teaches us appeared first on Microsoft Research.

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