Fuzzy matching learning for dynamic resource allocation in cellular V2X network

C Fan, B Li, Y Wu, J Zhang, Z Yang… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Benefiting from the global deployment and fast commercialization of cellular systems,
cellular-enabled vehicle-to-everything (V2X) opens up a significant prospect in the …

A comprehensive review on internet of things task offloading in multi-access edge computing

W Dayong, KBA Bakar, B Isyaku, TAE Eisa… - Heliyon, 2024 - cell.com
With the rapid development of Internet of Things (IoT) technology, Terminal Devices (TDs)
are more inclined to offload computing tasks to higher-performance computing servers …

Geolocation-centric information platform for resilient spatio-temporal content management

K Tsukamoto, H Tamura, Y Taenaka… - IEICE Transactions …, 2021 - search.ieice.org
In IoT era, the growth of data variety is driven by cross-domain data fusion. In this paper, we
advocate that “local production for local consumption (LPLC) paradigm” can be an …

Optimal resource allocation for multi-user OFDMA-URLLC MEC systems

WR Ghanem, V Jamali… - IEEE Open Journal of the …, 2022 - ieeexplore.ieee.org
In this paper, we study resource allocation algorithm design for multi-user orthogonal
frequency division multiple access (OFDMA) ultra-reliable low latency communication …

ODTRA-Based Task Offload Optimisation For IIoT Systems: Improving Efficiency And Performance With Digital Twins And Metaheuristic Optimisation

D Swaminathan, A Rajagopalan, N Venkatram… - IEEE …, 2024 - ieeexplore.ieee.org
The Industrial Internet of Things (IIoT) has revolutionized several industries by improving the
communication of sensor data among interconnected machines and systems. IIoT …

FUNOff: Offloading Applications At Function Granularity for Mobile Edge Computing

X Chen, M Li, H Zhong, X Chen, Y Ma… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Mobile edge computing (MEC) offers a promising technology that deploys computing
resources closer to mobile devices for improving performance. Most of the existing studies …

Joint Optimization of Transmission and Computation Resources for Rechargeable Multi-Access Edge Computing Networks

C Liu, JB Wang, C Zeng, Y Chen… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Multi-access edge computing (MEC) and wireless power transfer (WPT) have emerged as
promising paradigms to address the bottlenecks of computing power and battery capacity of …

Divisible Task Offloading for Multiuser Multiserver Mobile Edge Computing Systems based on Deep Reinforcement Learning

L Tang, H Qin - IEEE Access, 2023 - ieeexplore.ieee.org
Mobile edge computing (MEC) is a promising computing paradigm that enables offloading
tasks to edge servers to decrease the load on user equipment (UE) and the latency of …

Deep reinforcement learning edge workload orchestrator for vehicular edge computing

EN Silva, FM Da Silva - 2023 IEEE 9th International …, 2023 - ieeexplore.ieee.org
Smart vehicles in Vehicular Edge Computing Environments run latency sensitive
applications, such as driver assistance, autonomous driving, accident prevention and others …

Energy-efficient anomaly detection with primary and secondary attributes in edge-cloud collaboration networks

X Li, Z Zhou, Z Shi, X Xue… - IEEE Internet of Things …, 2021 - ieeexplore.ieee.org
An energy-efficient anomaly detection is fundamental to maintain a healthy status of domain
applications in edge-cloud collaboration networks. Generally, various kinds of multimodal …