A computation offloading scheme for energy consumption optimization in Internet of vehicles

Wenxuan GAO; Xinjie YANG

doi:10.11959/j.issn.1000-0801.2023189

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A computation offloading scheme for energy consumption optimization in Internet of vehicles

Research and Development | 更新时间：2024-06-05

- A computation offloading scheme for energy consumption optimization in Internet of vehicles
- Telecommunications Science Vol. 39, Issue 10, Pages: 29-40(2023)
- 作者机构：
  
  1. 宁波大学信息科学与工程学院，浙江宁波 315211
  2. 网络与交换技术全国重点实验室（北京邮电大学），北京 100876
- 作者简介：
- 基金信息：
- DOI：10.11959/j.issn.1000-0801.2023189
  CLC： TP393
- Published Online：2023-10，
  
  Published：20 October 2023
- 稿件说明：
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Wenxuan GAO, Xinjie YANG. A computation offloading scheme for energy consumption optimization in Internet of vehicles[J]. Telecommunications science, 2023, 39(10): 29-40.
DOI：

Wenxuan GAO, Xinjie YANG. A computation offloading scheme for energy consumption optimization in Internet of vehicles[J]. Telecommunications science, 2023, 39(10): 29-40. DOI： 10.11959/j.issn.1000-0801.2023189.

摘要

车联网环境下面向车辆的应用普遍具有计算密集和时延敏感等特性，引入移动车辆闲置计算资源作为网络算力的补充，可有效缓解边缘服务器的计算负载压力。针对车联网环境中边缘计算卸载的任务分配问题，充分利用RSU、用户车辆和RSU服务范围内移动车辆的计算资源组合，提出一种基于麻雀搜索算法的计算卸载方案（sparrow search based computation offloading scheme，S

COS），用以优化整体系统能耗。此外，该方案充分考虑了车辆移动性带来的服务时间限制以及计算节点出现故障的可能性等现实问题。仿真结果表明， S

COS在处理计算密集和时延敏感型任务时可以满足任务时延要求，并且能够显著降低系统能耗。

Abstract

In Internet of vehicles (IoV)

vehicle-oriented applications are generally computation-intensive and latency-sensitive.Introducing idle computing resources from mobile vehicles as a supplement to network computing power can effectively alleviate the load pressure on edge servers.The problem of task allocation for edge computation offloading in the context of IoV environment were researched.By fully leveraging the combined computing resources of roadside units (RSU)

user vehicles

and mobile vehicles within the RSU service range

a computation offloading strategy based on the sparrow search algorithm was proposed and referred to as sparrow search based computation offloading scheme (S

COS)

aiming to optimize the overall system energy consumption.In addition

this strategy fully taked into account practical network issues such as service time constraints caused by vehicle mobility and the potential occurrence of computation node failures.The simulation results demonstrate that S

COS can meet the latency requirements for computation-intensive and latency-sensitive tasks

while significantly reducing system energy consumption.

关键词

Keywords

references

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