Submit

Login Login

Register Register

Home / Journals / CMC / Online First / doi:10.32604/cmc.2026.086401
Journal Menu
Special Issues
Table of Content

All issues

Online First

2026

2025

2024

2023

2022

2021

2020

2019

2018

2017

2016

2015

2014

2013

2012

2011

2010

2009

2008

2007

2006

2005

2004

Open Access

ARTICLE

Age-Energy Tradeoff in Vehicular MEC: Sensing, Transmission, and Computation Co-Optimization

Hui Zhang1, Mangang Xie1,*, Baozhen An2, Jing Wei1
1 College of Artificial Intelligence and Computer Science, Northwest Normal University, No. 967 Anning East Road, Anning District, Lanzhou, China
2 School of Information Science and Engineering, Lanzhou University, No. 222, Tianshui South Road, Chengguan District, Lanzhou, China
* Corresponding Author: Mangang Xie. Email: email

Computers, Materials & Continua https://doi.org/10.32604/cmc.2026.086401

Received 29 May 2026; Accepted 30 July 2026; Published online 13 August 2026

Abstract

Peak age of information (PAoI) and energy consumption (EC) are conflicting yet critical metrics in mobile edge computing (MEC)-assisted vehicular networks. Most existing studies overlook the joint effects of sensing, transmission, and computation. The main contributions of this work are threefold. First, we derive novel analytical expressions for the average PAoI and average EC under all three strategies, explicitly accounting for the energy and delay costs across the entire data processing chain. Second, we demonstrate that the partial computation offloading strategy is superior, effectively balancing the low latency of local processing with the high power of edge computing. Third, we formulate a weighted optimization problem to navigate the PAoI-EC tradeoff and identify an optimal offloading ratio that dynamically adapts to specific freshness and efficiency requirements. Numerical results demonstrate that jointly optimizing the offloading ratio, edge computing capability, and transmission power significantly improves performance. Our findings offer practical guidelines for designing timely and energy-efficient vehicular telematics systems.

Keywords

Peak age of information; energy consumption; mobile edge computing; vehicular telematics; partial computation offloading

  • 150

    View

  • 37

    Download

  • 0

    Like

Related articles
Copyright© 2026 Tech Science Press
© 1997-2026 TSP (Henderson, USA) unless otherwise stated

Share Link