Resource allocation

In this paper, we propose a novel resource management scheme that jointly allocates the transmit
power and computational resources in a centralized radio access network architecture. The network
comprises a set of computing nodes to which the requested tasks of different users are offloaded. The
optimization problem minimizes the energy consumption of task offloading while takes the end-to-end latency, i.e., the transmission, execution, and propagation latencies of each task, into account. We aim to

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The simulation code for the paper:

"AoI-Aware Resource Allocation for Platoon-Based C-V2X Networks via Multi-Agent Multi-Task Reinforcement Learning"

 

The overall architecture of the proposed MARL framework is shown in the figure.

 

Modified MADDPG: This algorithm trains two critics (different from legacy MADDPG) with the following functionalities:

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# -*- coding: utf-8 -*-

"""

Created on Wed Feb 26 11:19:38 2020

 

@author: ali nouruzi

"""

 

import numpy as np

import random

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This dataset contains the database of the transport block (TB) configurations .

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Smart Grids (SG) are a novel paradigm introduced for optimizing the management of the power generation, transmission, distribution and consumption. A SG system can efficiently work only if all the components are connected through a communication network able to satisfy the SG applications requirements. Wireless communications are the most appropriate candidates for handling SG requirements due to their flexibility.

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Smart Grids (SG) are a novel paradigm introduced for optimizing the management of the power generation, transmission, distribution and consumption. A SG system can efficiently work only if all the components are connected through a communication network able to satisfy the SG applications requirements. Wireless communications are the most appropriate candidates for handling SG requirements due to their flexibility.

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