Jing Huang, Wenyu Wu, Weihong Huang, Yufeng Xiao, Lisi F. Lisi, Jinxi Sun
{"title":"A Survey on Task Partitioning and Scheduling for Vehicular Edge Computing","authors":"Jing Huang, Wenyu Wu, Weihong Huang, Yufeng Xiao, Lisi F. Lisi, Jinxi Sun","doi":"10.1109/CSCloud-EdgeCom58631.2023.00064","DOIUrl":null,"url":null,"abstract":"Vehicle edge computing (VEC) has become an important research field in recent years. In VEC, computation offloading moves computationally intensive tasks from resource-constrained devices to the network edge, it provides service closer to the end-users. By processing tasks with abundant idle resources at the network edge, low-latency demands for some tasks can be met. However, the mobility and uncertainty of vehicles pose significant challenges to vehicle computation offloading. This paper focuses on the decision-making process of vehicle computation offloading, specifically task partitioning and scheduling decisions. This paper summarizes some hot problems and solutions, including latency optimization, reliability optimization, energy efficiency optimization, cost optimization, and mobility support. This study will help researchers discover important features of vehicle computation offloading and find the most suitable scheme to solve the vehicle offloading problem in different scenarios.","PeriodicalId":56007,"journal":{"name":"Journal of Cloud Computing-Advances Systems and Applications","volume":"1 1","pages":"336-342"},"PeriodicalIF":3.7000,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Cloud Computing-Advances Systems and Applications","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1109/CSCloud-EdgeCom58631.2023.00064","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 1
Abstract
Vehicle edge computing (VEC) has become an important research field in recent years. In VEC, computation offloading moves computationally intensive tasks from resource-constrained devices to the network edge, it provides service closer to the end-users. By processing tasks with abundant idle resources at the network edge, low-latency demands for some tasks can be met. However, the mobility and uncertainty of vehicles pose significant challenges to vehicle computation offloading. This paper focuses on the decision-making process of vehicle computation offloading, specifically task partitioning and scheduling decisions. This paper summarizes some hot problems and solutions, including latency optimization, reliability optimization, energy efficiency optimization, cost optimization, and mobility support. This study will help researchers discover important features of vehicle computation offloading and find the most suitable scheme to solve the vehicle offloading problem in different scenarios.
期刊介绍:
The Journal of Cloud Computing: Advances, Systems and Applications (JoCCASA) will publish research articles on all aspects of Cloud Computing. Principally, articles will address topics that are core to Cloud Computing, focusing on the Cloud applications, the Cloud systems, and the advances that will lead to the Clouds of the future. Comprehensive review and survey articles that offer up new insights, and lay the foundations for further exploratory and experimental work, are also relevant.