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Showing 1 to 15 of 15 for “"Mobile Edge Computing"”.

  1. Deep learning for DDoS attack detection in mobile edge computing

    Mobile edge computing (MEC) has become a disruptive technology that brings computation closer to end users, reducing latency and allowing faster response times. However, MEC like other networks is facing cyber security issues, particularly the Distributed Denial of Service attack (DDoS) which has …

    wlv Repository record for Deep learning for DDoS attack detection in mobile edge computing (opens in a new tab)

  2. Machine Learning Approach for Resource Allocation in Mobile Edge Computing

    <p>Mobile Edge Computing (MEC) is recognized as a pivotal technology supporting cloud computing and innovative services at the network edge, offering significant reductions in system delay and mitigating network traffic congestion. It supports latency-sensitive applications like Augmented Reality …

    cuny Repository record for Machine Learning Approach for Resource Allocation in Mobile Edge Computing (opens in a new tab)

  3. Edge Computing: challenges, solutions and architectures arising from the integration of Cloud Computing with Internet of Things

    … In order to meet these growing needs, the computing power and storage space are transferred to the network edge to reduce the network latency and increase the bandwidth availability. Edge computing allows to approach high-bandwidth content and sensitive apps to the user or data source and …

    catania Repository record for Edge Computing: challenges, solutions and architectures arising from the integration of Cloud Computing with Internet of Things (opens in a new tab)

  4. Collaborative Autonomy of Multi-Agent Aerial Systems for Future Disaster Response

    … 5 introduces a fully decentralized UAV-assisted mobile edge computing framework consisting of a K-Grouped Soft Actor-Critic with Trajectory Planning (KGSAC-TP) algorithm for UAV and a User Switching Mechanism (USM) for heterogeneous users. Furthermore, Chapter 6 designed an Agentic …

    exeter

  5. Leveraging vehicular cloud computing through location and request prediction

    … Ad-hoc networks (VANET) has been acknowledged as a promising solution for monitoring road conditions. Despite the many benefits they can bring to society, the growing demand for communication, storage, and processing capabilities is giving rise to new challenges. For instance, the …

    uoit Repository record for Leveraging vehicular cloud computing through location and request prediction (opens in a new tab)

  6. Secure Networking and Efficient Computing in Unmanned Aerial Vehicle Assisted Green IoT Networks

    … struggle with limited energy, communication and computing resources. By combining UAVs with GIoT, the resultant system leverages the strengths of both: enhancing in situ data collection with UAVs' broad surveillance capabilities and GIoT's dense, ground truth data. In this study, we envision a …

    alabama Repository record for Secure Networking and Efficient Computing in Unmanned Aerial Vehicle Assisted Green IoT Networks (opens in a new tab)

  7. ML-Based Optimization of Large-Scale Systems: Case Study in Smart Microgrids and 5G RAN

    … joint radio and computation resource for mobile edge computing (MEC), joint radio and cache resource allocation for edge caching. Additionally, we further investigate how HRL can improve the energy efficiency (EE) of RIS-aided heterogeneous networks. The findings of this research highlight …

    ottawa-retro Repository record for ML-Based Optimization of Large-Scale Systems: Case Study in Smart Microgrids and 5G RAN (opens in a new tab)

  8. Unmanned Aerial Vehicles and Edge Computing in Wireless Networks

    … the enabling technologies in wireless networks, edge computing is proposed to offload users' computation tasks to edge servers to reduce users' latency and energy consumption. However, this requires efficient utilization of both communication resources and computation resources. Furthermore, …

    vt Repository record for Unmanned Aerial Vehicles and Edge Computing in Wireless Networks (opens in a new tab)

  9. Data Traffic Modelling in Mobile Networks for Heterogeneous Types of IoT Services

    The upcoming 5th Generation (5G) mobile networks will be different from the previous mobile network generations in the fact that it will enable the mobile networks industry, besides offering superior broadband services, to enhance Internet of Things (IoT) industries such as vehicular communication …

    liverpool-jm Repository record for Data Traffic Modelling in Mobile Networks for Heterogeneous Types of IoT Services (opens in a new tab)

  10. Joint Task Offloading and Resource Allocation for Mobile Cloud with Computing Access Point

    Mobile Cloud Computing (MCC) extends the capabilities of mobile devices to improve user experience. Mobile users can offload tasks to the cloud, using abundant cloud resources to help them gather, store, and process data. In this dissertation, we consider a general three-tier multi-user MCC system …

    toronto-retro Repository record for Joint Task Offloading and Resource Allocation for Mobile Cloud with Computing Access Point (opens in a new tab)

  11. Complexity for Edge Intelligence in 6G

    … fondamentale è quella di Multi Access Edge Computing (MEC) che rappresenta una tecnologia abilitante al fine di costruire la cosiddetta “edge intelligence” di rete distribuita e collettiva, puntando su meccanismi di trasferimento di attività computazionali tra i nodi edge (offloading) …

    catania Repository record for Complexity for Edge Intelligence in 6G (opens in a new tab)

  12. Coping Uncertainty in Wireless Network Optimization

    … role in 5G/next-G networks, which requires knowledge of network parameters (e.g., channel state information). The majority of existing works assume that all network parameters are either given a prior or can be accurately estimated. However, in many practical scenarios, some parameters are …

    vt Repository record for Coping Uncertainty in Wireless Network Optimization (opens in a new tab)

  13. The design and optimization of cooperative mobile edge

    … such that they can function as standalone mobile computing units with multiple wireless network interfaces. At the network end, various facilities are also pushed to the mobile edge to foster internet connections. Distributed small scale cloud resources and green energy harvesters can be …

    njit Repository record for The design and optimization of cooperative mobile edge (opens in a new tab)