Mar 1, 2022 · Abstract: Mobile network operators (MNOs) allocate computing and caching resources for mobile users by deploying a central control system.
To solve this problem, in this article, we design a joint computing and caching framework by integrating deep deterministic policy gradient (DDPG) algorithm.
The final simulation result shows that our solution can reduce energy costs by more than 15% while ensuring the tasks can be completed on time. Index Terms—Deep ...
Aug 19, 2024 · Deep reinforcement learning (DRL) offers a promising solution by balancing resource utilization, latency, and energy optimization. However, ...
This paper constructs a three-layer offloading framework in intelligent Internet of Vehicles (IoV) to minimize the overall energy consumption while satisfying ...
Vehicular edge computing (VEC) effectively reduces the computational burden on vehicles by offloading tasks from resource-constrained vehicles to edge nodes ...
Nov 1, 2023 · Simulation results show that ECO-SDIoT can effectively reduce task completion time and energy consumption compared with other strategies.
To overcome the limitation, mobile edge computing (MEC) is an emerging paradigm that provides fast and energy-efficient computing services for vehicle users [5] ...
A three-layer offloading framework in intelligent Internet of Vehicles (IoV) to minimize the overall energy consumption while satisfying the delay ...
This paper proposes a communication task allocation algorithm based on deep reinforcement learning for vehicle-to-pedestrian communication scenarios in edge ...