Task co-offloading for D2D-assisted mobile edge computing in industrial internet of things
Mobile edge computing (MEC) and device-to-device (D2D) offloading are two promising
paradigms in the industrial Internet of Things (IIoT). In this article, we investigate task co …
paradigms in the industrial Internet of Things (IIoT). In this article, we investigate task co …
CoopEdge+: Enabling decentralized, secure and cooperative multi-access edge computing based on blockchain
Multi-access Edge Computing (MEC) has emerged as a new distributed computing
paradigm for its ability to offer low-latency services to users. Suffering from constrained …
paradigm for its ability to offer low-latency services to users. Suffering from constrained …
Low-latency edge video analytics for on-road perception of autonomous ground vehicles
To improve the transportation efficiency of advanced manufacturing, cameras have been
extensively deployed to enhance the on-road perception of autonomous ground vehicles in …
extensively deployed to enhance the on-road perception of autonomous ground vehicles in …
Two-tiered online optimization of region-wide datacenter resource allocation via deep reinforcement learning
This paper addresses the important need for advanced techniques in continuously
allocating workloads on shared infrastructures in data centers, a problem arising due to the …
allocating workloads on shared infrastructures in data centers, a problem arising due to the …
A survey on integrated computing, caching, and communication in the cloud-to-edge continuum
Cloud and edge computing have proposed different functionalities to enable multiple
applications requiring different communication, computing, and caching (3C) resources. The …
applications requiring different communication, computing, and caching (3C) resources. The …
Performance Analysis of Fault-Tolerant Multiagent Coordination Mechanisms
R Pinciroli, C Trubiani - IEEE Transactions on Industrial …, 2023 - ieeexplore.ieee.org
Performance evaluation of multiagent systems (MAS) embraces several challenges due to
uncertain operational environments, such as software/hardware failures and unfaithful …
uncertain operational environments, such as software/hardware failures and unfaithful …
A Hybrid Deep Reinforcement Learning Approach for Jointly Optimizing Offloading and Resource Management in Vehicular Networks
CL Chen, B Bhargava, V Aggarwal… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
Satisfying the quality of service of data-intensive autonomous driving applications has
become challenging. In this work, we propose a novel methodology that optimizes …
become challenging. In this work, we propose a novel methodology that optimizes …
Task execution latency minimization for energy-sensitive IoTs in wireless powered mobile edge computing: A DRL-based method
Wireless powered mobile edge computing (MEC) has become a vital component of future
6G networks, offering efficient computational capabilities to internet of things (IoT) devices …
6G networks, offering efficient computational capabilities to internet of things (IoT) devices …
Game-Based Computation Offloading and Power Allocation for LEO Constellation Networks in Distributed and Dynamic Environment
Y Gao, Z Ji, K Zhao, T De Cola… - IEEE Internet of Things …, 2023 - ieeexplore.ieee.org
To build the new generation of ubiquitous communication and service integration networks
with “network omnipresence and computing ubiquitous,” it is urgent to improve the in-orbit …
with “network omnipresence and computing ubiquitous,” it is urgent to improve the in-orbit …
Latency Estimation and Computational Task Offloading in Vehicular Mobile Edge Computing Applications
Mobile edge computing (MEC) is a key enabler of time-critical vehicle-to-everything (V2X)
applications. Under MEC, a vehicle has the option to offload computationally intensive tasks …
applications. Under MEC, a vehicle has the option to offload computationally intensive tasks …