دورية أكاديمية
Computation offloading through mobile vehicles in IoT-edge-cloud network
| العنوان: | Computation offloading through mobile vehicles in IoT-edge-cloud network |
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| المؤلفون: | Jun Long, Yueyi Luo, Xiaoyu Zhu, Entao Luo, Mingfeng Huang |
| المصدر: | EURASIP Journal on Wireless Communications and Networking, Vol 2020, Iss 1, Pp 1-21 (2020) |
| بيانات النشر: | SpringerOpen, 2020. |
| سنة النشر: | 2020 |
| المجموعة: | LCC:Telecommunication LCC:Electronics |
| مصطلحات موضوعية: | Computation offloading, Mobile vehicles, IoT-edge-cloud network, Deep reinforcement learning, Telecommunication, TK5101-6720, Electronics, TK7800-8360 |
| الوصف: | Abstract With the developing of Internet of Things (IoT) and mobile edge computing (MEC), more and more sensing devices are widely deployed in the smart city. These sensing devices generate various kinds of tasks, which need to be sent to cloud to process. Usually, the sensing devices do not equip with wireless modules, because it is neither economical nor energy saving. Thus, it is a challenging problem to find a way to offload tasks for sensing devices. However, many vehicles are moving around the city, which can communicate with sensing devices in an effective and low-cost way. In this paper, we propose a computation offloading scheme through mobile vehicles in IoT-edge-cloud network. The sensing devices generate tasks and transmit the tasks to vehicles, then the vehicles decide to compute the tasks in the local vehicle, MEC server or cloud center. The computation offloading decision is made based on the utility function of the energy consumption and transmission delay, and the deep reinforcement learning technique is adopted to make decisions. Our proposed method can make full use of the existing infrastructures to implement the task offloading of sensing devices, the experimental results show that our proposed solution can achieve the maximum reward and decrease delay. |
| نوع الوثيقة: | article |
| وصف الملف: | electronic resource |
| اللغة: | English |
| تدمد: | 1687-1499 |
| Relation: | https://doaj.org/toc/1687-1499 |
| DOI: | 10.1186/s13638-020-01848-5 |
| URL الوصول: | https://doaj.org/article/8c220148bb634832a2ed367c012a03b6 |
| رقم الأكسشن: | edsdoj.8c220148bb634832a2ed367c012a03b6 |
| قاعدة البيانات: | Directory of Open Access Journals |
Find this article in full text from Springer Verlag. 
Full Text Finder | تدمد: | 16871499 |
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| DOI: | 10.1186/s13638-020-01848-5 |