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Showing 1 to 6 of 6 for “"Edge networks"”.

  1. Distributed Machine Learning in Heterogeneous Edge Networks

    The development of edge devices (e.g., smartphones, IoT sensors, and wearables) has led to a surge in data generated at the network's edge. Meanwhile, the complexity of machine learning models has increased significantly, with state-of-the-art models for tasks like natural language processing and …

    unr Repository record for Distributed Machine Learning in Heterogeneous Edge Networks (opens in a new tab)

  2. Application-specific transfer learning over edge networks

    … techniques and transfer learning approaches over edge networks to enhance the performance and networking latency within discrete nodes. Edge networks are widely used to improve the efficiency and staging of any algorithm as the embedded systems focus on implementing some particular events based on …

    uoit Repository record for Application-specific transfer learning over edge networks (opens in a new tab)

  3. Computational Offloading for Real-Time Computer Vision in Unreliable Multi-Tenant Edge Systems

    … in serving Computer Vision applications at the Edge, where Edge Devices generate vast quantities of data, clashes with the reality that many Devices are largely unable to process their data in real time. While computational offloading, not to the Cloud but to nearby Edge Nodes, offers convenient …

    vt Repository record for Computational Offloading for Real-Time Computer Vision in Unreliable Multi-Tenant Edge Systems (opens in a new tab)

  4. Scaled: Scalable Federated Learning via Distributed Hash Table Based Overlays

    … communication and aggregation of mil- lions of edge devices. In this paper, we propose Scalable Federated Learning via Distributed Hash Table Based Overlays for network (Scaled) to conduct multiple concurrently running FL-based applications over edge networks. Specifically, Scaled adopts a fully …

    vt Repository record for Scaled: Scalable Federated Learning via Distributed Hash Table Based Overlays (opens in a new tab)

  5. Resource Optimization Strategies and Optimal Architectural Design for Ultra-Reliable Low-Latency Applications in Multi-Access Edge Computing

    … this evolution focuses on ultra-dense edge networks with multi-access edge computing (MEC) facilities. MEC emerges as a solution, placing resourceful servers closer to users. However, the dynamic nature of processing and interaction patterns necessitates effective network control, which …

    trento Repository record for Resource Optimization Strategies and Optimal Architectural Design for Ultra-Reliable Low-Latency Applications in Multi-Access Edge Computing (opens in a new tab)

  6. Online Optimization for Edge Computing under Uncertainty in Wireless Networks

    Edge computing is an emerging technology that can overcome the limitations of centralized cloud computing by enabling distributed, low-latency computation at a network edge. Particularly, in edge computing, some of the cloud's functionalities such as storage, processing, and computing are migrated …

    vt Repository record for Online Optimization for Edge Computing under Uncertainty in Wireless Networks (opens in a new tab)