한국인터넷정보학회 논문지
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| 한글제목(Korean Title) |
Deep Neural Network-Based Critical Packet Inspection for Improving Traffic Steering in Software-Defined IoT |
| 영문제목(English Title) |
Deep Neural Network-Based Critical Packet Inspection for Improving Traffic Steering in Software-Defined IoT |
| 저자(Author) |
담프로힘
맛사
김석훈
Prohim Tam
Sa Math
Seokhoon Kim
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| 원문수록처(Citation) |
VOL 22 NO. 6 PP. 0001 ~ 0008 (2021. 12) |
한글내용
(Korean Abstract) |
|
영문내용
(English Abstract) |
With the rapid growth of intelligent devices and communication technologies, 5G network environment has become more heterogeneous and complex in terms of service management and orchestration. 5G architecture requires supportive technologies to handle the existing challenges for improving the Quality of Service (QoS) and the Quality of Experience (QoE) performances. Among many challenges, traffic steering is one of the key elements which requires critically developing an optimal solution for smart guidance, control, and reliable system. Mobile edge computing (MEC), software-defined networking (SDN), network functions virtualization (NFV), and deep learning (DL) play essential roles to complementary develop a flexible computation and extensible flow rules management in this potential aspect. In this proposed system, an accurate flow recommendation, a centralized control, and a reliable distributed connectivity based on the inspection of packet condition are provided. With the system deployment, the packet is classified separately and recommended to request from the optimal destination with matched preferences and conditions. To evaluate the proposed scheme outperformance, a network simulator software was used to conduct and capture the end-to-end QoS performance metrics. SDN flow rules installation was experimented to illustrate the post control function corresponding to DL-based output. The intelligent steering for network communication traffic is cooperatively configured in SDN controller and NFV-orchestrator to lead a variety of beneficial factors for improving massive real-time Internet of Things (IoT) performance. |
| 키워드(Keyword) |
Deep Learning
Deep Packet Inspection
Network Functions Virtualization
Software-Defined Networking
Traffic Steering
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| 파일첨부 |
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