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VNF Anomaly Detection Method based on Unsupervised Machine Learning
Seondong Heo, Seunghoon Jeong, Hosang Yun
http://doi.org/10.5626/JOK.2022.49.9.780
By applying virtualization technology to telecommunication networks, it is possible to reduce hardware dependencies and provide flexible control and management to the operators. In addition, since Capital Expenditure (CAPEX) and Operating Expenditure (OPEX) can be reduced by utilizing the technology, modern telco operators and service providers are using Software-Defined Networking(SDN) and Network Function Virtualization (NFV) technology to provide services more efficiently. As SDN and NFV are widely used, cyber attacks on Vitualized Network Functions (VNF) that degrade the quality of service or cause service denial are increasing. In this study, we propose a VNF anomaly detection method based on unsupervised machine learning techniques that models the steady states of VNFs and detects abnormal states caused by cyber attacks.
Traffic Steering System with Dual Connectivity for Video Streaming Services
Gi Seok Park, Hyunmin Noh, Jae Jun Ha, Hyung Jun Kim, Sang Heon Shin, Dong Hyun Kim, Jong Hwan Ko, Jeung Won Choi, Hwangjun Song
http://doi.org/10.5626/JOK.2019.46.6.577
In this paper, we propose a traffic steering system with dual connectivity to provide stable video streaming services for users by steering portion of the macrocell traffic into small cells. The proposed system achieves a good balance between fairness and social welfare in terms of video quality by allocating the radio resource of the macro base station. The user data flow is divided into two channels toward the macro base station and the small cell AP, and the users receive their data from both. In the proposed system, the fountain code is adopted to overcome practical issues in the dual connectivity. Moreover, the SDN is employed not only to rapidly react to time-varying network condition, but also to control network resources efficiently. The proposed system is implemented using NS-3. The simulation results show that the proposed system can achieve much better performance compared with existing traffic steering algorithms.
SDN based Mobility Management in IoT Networks
BoYeong Mun, SungChol Cho, Shimin SUN, Jin Xinan Shu, Cheongbin Kim, JunHyuk Kim, Sunyoung Han
http://doi.org/10.5626/JOK.2018.45.7.733
IoT environments are constrained by various factors, including object address, battery, network bandwidth, and computing power. We propose a system to manage mobility by applying an SDN (Software Defined Networking) centralized management method to effectively solve the problems caused by moving IoT terminals. The SDN used in this paper is programmable, which facilitates its scalability as well as its ability to manage various IoT terminals. in this paper, we propose a mobility architecture using SDN for IoT, and design as well as implement a system based on it.
Fog-Server Placement Technique Based on Network Edge Area Traffic for a Fog-Computing Environment
Min-Sik Son, Sang-Hwa Chung, Won-Suk Kim
http://doi.org/10.5626/JOK.2018.45.6.598
Cloud computing is now widely used. However, cloud computing alone cannot adequately respond to the traffic patterns generated by various objects in the new network environment of the internet of things (IoT). Fog computing is one method for overcoming and solving the problems of cloud computing. A fog-server placement method is needed, including a mechanism for determining the location for a fog-server that can provide services. However, most studies only consider the fog device’s computing resources, and the locations of the client and the data sources are not considered; therefore, the network situation becomes worse after the fog-server placement. In this paper, we propose a technique for fog-server placement that considers traffic generation in relation to the locations of the clients and data sources. In the experiment, clients and data sources are concentrated or distributed in the network topology, and their corresponding network-traffic patterns are considered. Experimental results show that, in terms of reducing core network traffic and memory usage, placing the fog server according to the proposed network traffic conditions is more efficient than placing fog servers in all of the fog devices.
LTRE: Lightweight Traffic Redundancy Elimination in Software-Defined Wireless Mesh Networks
Gwangwoo Park, Wontae Kim, Joonwoo Kim, Sangheon Pack
http://doi.org/10.5626/JOK.2017.44.9.976
Wireless mesh network (WMN) is a promising technology for building a cost-effective and easily-deployed wireless networking infrastructure. To efficiently utilize limited radio resources in WMNs, packet transmissions (particularly, redundant packet transmissions) should be carefully managed. We therefore propose a lightweight traffic redundancy elimination (LTRE) scheme to reduce redundant packet transmissions in software-defined wireless mesh networks (SD-WMNs). In LTRE, the controller determines the optimal path of each packet to maximize the amount of traffic reduction. In addition, LTRE employs three novel techniques: 1) machine learning (ML)-based information request, 2) ID-based source routing, and 3) popularity-aware cache update. Simulation results show that LTRE can significantly reduce the traffic overhead by 18.34% to 48.89%.
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