Design and Application of a Resource Allocation Method for CAEVs Internet of Things Based on Swarm Intelligence Computing-Reference-Cited by-同舟云学术

Design and Application of a Resource Allocation Method for CAEVs Internet of Things Based on Swarm Intelligence Computing

Published:2023-07-07 Issue:13 Volume:12 Page:2997
ISSN:2079-9292
Container-title:Electronics
language:en
Short-container-title:Electronics

Author:

Han Yibo¹,Zhang Zheng²,Han Pu³,Yuan Bo⁴,Liu Lu⁴,Panneerselvam John⁴

Affiliation:

1. Nanyang Research Institute of Big Data, Nanyang Institute of Technology, Nanyang 473004, China

2. School of Computer and Software, Nanyang Institute of Technology, Nanyang 473004, China

3. School of Information Engineering, Nanyang Institute of Technology, Nanyang 473004, China

4. Department of Informatics, University of Leicester, University Rd, Leicester LE1 7RH, UK

Abstract

The Internet of Things (IoT) faces significant challenges in the requirements of sensitive task latency, reasonable resource allocation and reliability for resource transactions. This paper introduces a novel method for road resource allocation in the IoT context of connected and autonomous electric vehicles (CAEVs). The proposed algorithm leverages the ant colony algorithm (ACA) to effectively allocate and coordinate road resources within groups of CAEVs. By considering the energy consumption and pheromone volatilization, the allocation and coordination process of road resources are optimized. To improve the linear packet loss of RED, we adopt the advanced ACA and CRED in the NS2 platform. The experimental results demonstrate that the proposed method outperforms the RED algorithm in packet loss rate and delay time, significantly enhancing system efficiency and performance. Furthermore, the combination of the CRED algorithm and ant colony algorithm successfully mitigates short-term congestion and identifies optimized paths with minimal delay.

Funder

Henan Science and Technology Plan Project

Publisher

MDPI AG

Subject

Electrical and Electronic Engineering,Computer Networks and Communications,Hardware and Architecture,Signal Processing,Control and Systems Engineering

Link

https://www.mdpi.com/2079-9292/12/13/2997/pdf

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