Service Function Chain Embedding for NFV-Enabled IoT Based on Deep Reinforcement Learning
| العنوان: | Service Function Chain Embedding for NFV-Enabled IoT Based on Deep Reinforcement Learning |
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| المؤلفون: | F. Richard Yu, Jingyu Wang, Jianxin Liao, Xiaoyuan Fu, Qi Qi |
| المصدر: | IEEE Communications Magazine. 57:102-108 |
| بيانات النشر: | Institute of Electrical and Electronics Engineers (IEEE), 2019. |
| سنة النشر: | 2019 |
| مصطلحات موضوعية: | Service (systems architecture), Computer Networks and Communications, Computer science, Distributed computing, 020206 networking & telecommunications, 02 engineering and technology, Service provider, Computer Science Applications, Server, 0202 electrical engineering, electronic engineering, information engineering, Embedding, Reinforcement learning, Business logic, Resource management, Electrical and Electronic Engineering, Virtual network |
| الوصف: | It is challenging to efficiently manage different resources in the IoT. Recently, Network function virtualization has attracted attention because of its prospect to achieve efficient resource management for IoT. In NFV-enabled IoT infrastructure, a service function chain (SFC) is composed of an ordered set of virtual network functions (VNFs) that are connected based on the business logic of service providers. However, the inefficiency of the SFC embedding process is one major problem due to the dynamic nature of IoT networks and the abundance of IoT terminals. In this article, we decompose the complex VNFs into smaller VNF components (VNFCs) to make more effective decisions since VNF nodes and physical network devices are usually heterogeneous. In addition, a deep reinforcement learning (DRL)-based scheme with experience replay and target network is proposed as a solution that can efficiently handle complex and dynamic SFC embedding scenarios. Simulation results present the efficient performance of the proposed DRL-based dynamic SFC embedding scheme. |
| تدمد: | 1558-1896 0163-6804 |
| URL الوصول: | https://explore.openaire.eu/search/publication?articleId=doi_________::f1cfdd041e84f2c89b32010bf4883d8a https://doi.org/10.1109/mcom.001.1900097 |
| حقوق: | CLOSED |
| رقم الأكسشن: | edsair.doi...........f1cfdd041e84f2c89b32010bf4883d8a |
| قاعدة البيانات: | OpenAIRE |
| تدمد: | 15581896 01636804 |
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