期刊
IEEE NETWORK
卷 33, 期 5, 页码 198-205出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/MNET.2019.1800309
关键词
Task analysis; Servers; Energy consumption; Processor scheduling; Energy efficiency; Scheduling; Delays
类别
资金
- State Key Laboratory of Integrated Services Networks, Xidian University [ISN20-01]
- China Postdoctoral Science Foundation [2018T110210]
- Fundamental Research Funds for the Central University [DUT19JC18]
- Fundacao para a Ciencia e a Tecnologia (FCT) [UID/EEA/50008/2019]
- RNP [01250.075413/2018-04]
- Centro de Referencia em Radiocomunicacoes (CRR) project of the Instituto Nacional de Telecomunicacoes (Inatel), Brazil
- Brazilian National Council for Research and Development (CNPq) [309335/2017-5]
Although modern transportation systems facilitate the daily life of citizens, the ever-increasing energy consumption and air pollution challenge the establishment of green cities. Current studies on green IoV generally concentrate on energy management of either battery-enabled RSUs or electric vehicles. However, computing tasks and load balancing among RSUs have not been fully investigated. In order to satisfy heterogeneous requirements of communication, computation and storage in IoVs, this article constructs an energy-efficient scheduling framework for MEC-enabled IoVs to minimize the energy consumption of RSUs under task latency constraints. Specifically, a heuristic algorithm is put forward by jointly considering task scheduling among MEC servers and downlink energy consumption of RSUs. To the best of our knowledge, this is a prior work to focus on the energy consumption control issues of MEC-enabled RSUs. Performance evaluations demonstrate the effectiveness of our framework in terms of energy consumption, latency and task blocking possibility. Finally, this article elaborates some major challenges and open issues toward energy-efficient scheduling in IoVs.
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