{"title":"海报:车辆网络中基于多排架构的动态任务调度","authors":"Tingting Xiao, Chen Chen, Qingqi Pei, Shaohua Wan","doi":"10.1109/ICDCS54860.2022.00135","DOIUrl":null,"url":null,"abstract":"The autonomous vehicle platoon has the potential to cope with the stress caused by the resource-constrained vehicles‘ demand for processing power and the spread-out deployment of MEC-BS. In this poster, we focus on a multi-platoons scenario for task scheduling. Our objective is to minimize the overall energy consumption subject to the long-term latency constraint. To characterize stochastic properties and deal with coupling between variables, we propose a dynamic task scheduling algorithm based on Lyapunov optimization (LDTS). We theoretically and empirically evaluate the performance of the proposed algorithm, which is illustrated to be significantly better than state-of-the-art and other benchmark approaches in terms of execution latency and energy consumption.","PeriodicalId":225883,"journal":{"name":"2022 IEEE 42nd International Conference on Distributed Computing Systems (ICDCS)","volume":"11 1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Poster: A Dynamic Task Scheduling using Multi-Platoon Architecture in Vehicular Networks\",\"authors\":\"Tingting Xiao, Chen Chen, Qingqi Pei, Shaohua Wan\",\"doi\":\"10.1109/ICDCS54860.2022.00135\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The autonomous vehicle platoon has the potential to cope with the stress caused by the resource-constrained vehicles‘ demand for processing power and the spread-out deployment of MEC-BS. In this poster, we focus on a multi-platoons scenario for task scheduling. Our objective is to minimize the overall energy consumption subject to the long-term latency constraint. To characterize stochastic properties and deal with coupling between variables, we propose a dynamic task scheduling algorithm based on Lyapunov optimization (LDTS). We theoretically and empirically evaluate the performance of the proposed algorithm, which is illustrated to be significantly better than state-of-the-art and other benchmark approaches in terms of execution latency and energy consumption.\",\"PeriodicalId\":225883,\"journal\":{\"name\":\"2022 IEEE 42nd International Conference on Distributed Computing Systems (ICDCS)\",\"volume\":\"11 1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 IEEE 42nd International Conference on Distributed Computing Systems (ICDCS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICDCS54860.2022.00135\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE 42nd International Conference on Distributed Computing Systems (ICDCS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICDCS54860.2022.00135","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Poster: A Dynamic Task Scheduling using Multi-Platoon Architecture in Vehicular Networks
The autonomous vehicle platoon has the potential to cope with the stress caused by the resource-constrained vehicles‘ demand for processing power and the spread-out deployment of MEC-BS. In this poster, we focus on a multi-platoons scenario for task scheduling. Our objective is to minimize the overall energy consumption subject to the long-term latency constraint. To characterize stochastic properties and deal with coupling between variables, we propose a dynamic task scheduling algorithm based on Lyapunov optimization (LDTS). We theoretically and empirically evaluate the performance of the proposed algorithm, which is illustrated to be significantly better than state-of-the-art and other benchmark approaches in terms of execution latency and energy consumption.