• KNOM Review
• /
• v.23 no.1
• /
• pp.34-42
• /
• 2020

Network Function Virtualization (NFV) environment can deal with dynamic changes in traffic status with appropriate deployment and scaling of Virtualized Network Function (VNF). However, determining and applying the optimal VNF deployment is a complicated and difficult task. In particular, it is necessary to predict the situation at a future point because it takes for the process to be applied and the deployment decision to the actual NFV environment. In this paper, we randomly generate service requests in Multiaccess Edge Computing (MEC) topology, then obtain training data for machine learning model from an Integer Linear Programming (ILP) solution. We use the simulation data to train the machine learning model which predicts the optimal VNF deployment in a predefined future point. The prediction model shows the accuracy over 90% compared to the ILP solution in a 5-minute future time point.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.16 no.11
• /
• pp.3584-3602
• /
• 2022

NFV realizes flexible and rapid software deployment and management of network functions in the cloud network, and provides network services in the form of chained virtual network functions (VNFs). However, using VNFs to provide quality guaranteed services is still a challenge because of the inherent difficulty in intelligently scaling VNFs to handle traffic fluctuations. Most existing works scale VNFs with fixed-capacity instances, that is they take instances of the same size and determine a suitable deployment location without considering the cloud network resource distribution. This paper proposes a traffic forecasted assisted proactive VNF scaling approach, and it adopts the instance capacity adaptive to the node resource. We first model the VNF scaling as integer quadratic programming and then propose a proactive adaptive VNF scaling (PAVS) approach. The approach employs an efficient traffic forecasting method based on LSTM to predict the upcoming traffic demands. With the obtained traffic demands, we design a resource-aware new VNF instance deployment algorithm to scale out under-provisioning VNFs and a redundant VNF instance management mechanism to scale in over-provisioning VNFs. Trace-driven simulation demonstrates that our proposed approach can respond to traffic fluctuation in advance and reduce the total cost significantly.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.12 no.2
• /
• pp.786-799
• /
• 2018

Recently, NFV has attracted attention as a next-generation network virtualization technology for hardware -independent and efficient utilization of resources. NFV is a technology that not only virtualize computing, server, storage, network resources based on cloud computing but also connect Multi-Tenant of VNFs, a software network function. Therefore, it is possible to reduce the cost for constructing a physical network and to construct a logical network quickly by using NFV. However, in NFV, when a new VNF is added to a running Tenant, authentication between VNFs is not performed. Because of this problem, it is impossible to identify the presence of Fake-VNF in the tenant. Such a problem can cause an access from malicious attacker to one of VNFs in tenant as well as other VNFs in the tenant, disabling the NFV environment. In this paper, we propose Auto-configurable Security Mechanism in NFV including authentication between tenant-internal VNFs, and enforcement mechanism of security policy for traffic control between VNFs. This proposal not only authenticate identification of VNF when the VNF is registered, but also apply the security policy automatically to prevent malicious behavior in the tenant. Therefore, we can establish an independent communication channel for VNFs and guarantee a secure NFV environment.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.16 no.5
• /
• pp.1708-1734
• /
• 2022

In the development of logistics system, the breakthrough of important technologies such as technology platform for logistics information management and control is the key content of the study. Based on Javascript and JQuery, the logistics system realizes real-time monitoring, collection of historical status data, statistical analysis and display, intelligent recommendation and other functions. In order to strengthen the cooperation of warehouse storage, enhance the utilization rate of resources, and achieve the purpose of real-time and visual supervision of transportation equipment and cargo tracking, this paper studies the VNF dynamic deployment and SFC routing problem in the network load change scenario based on the logistics system. The BIP model is used to model the VNF dynamic deployment and routing problem. The optimization objective is to minimize the total cost overhead generated by each SFCR. Furthermore, the application of the SFC mapping algorithm in the routing topology solving problem is proposed. Based on the concept of relative cost and the idea of topology transformation, the SFC-map algorithm can efficiently complete the dynamic deployment of VNF and the routing calculation of SFC by using multi-layer graph. In the simulation platform based on the logistics system, the proposed algorithm is compared with VNF-DRA algorithm and Provision Traffic algorithm in the network receiving rate, throughput, path end-to-end delay, deployment number, running time and utilization rate. According to the test results, it is verified that the test results of the optimization algorithm in this paper are obviously improved compared with the comparison method, and it has higher practical application and promotion value.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2017.11a
• /
• pp.102-105
• /
• 2017

최근 네트워크 서비스 관리의 복잡성을 줄이기 위해 새로운 네트워크 인프라가 등장하고 있다. NFV(Network Function Virtualization) 기술은 하드웨어 기반의 네트워크 장비에 가상화를 적용하여, 유연성 있는 네트워크 서비스를 제공한다. 네트워크 서비스는 Firewall, Parental Control (PC)과 같은 일련의 VNF (Virtual Network Function)로 구성된다. NFV 기술을 기존의 네트워크 환경과 통합시키는 경우 해결해야 할 난제가 존재한다. 기존 네트워크는 복잡성이 요구되며 많은 양의 트래픽을 다루어야 한다. 사용자가 요청한 네트워크 서비스의 높은 트래픽 로드로 인해 패킷 손실이 발생할 수 있다. 본 논문에서는 Zabbix 모니터링 시스템을 활용해 VNF 로드 기반의 Auto-scaling을 제안한다. 이를 통해 네트워크 서비스의 자원 효율성을 향상시키고 패킷 손실 비율을 줄일 수 있다.

• KNOM Review
• /
• v.24 no.1
• /
• pp.1-12
• /
• 2021

VM (Virtual Machine) live migration is a server virtualization technique for deploying a running VM to another server node while minimizing downtime of a service the VM provides. Currently, in cloud data centers, VM live migration is widely used to apply load balancing on CPU workload and network traffic, to reduce electricity consumption by consolidating active VMs into specific location groups of servers, and to provide uninterrupted service during the maintenance of hardware and software update on servers. It is critical to use VMlive migration as a prevention or mitigation measure for possible failure when its indications are detected or predicted. In this paper, we propose two VNF live migration methods; one for predictive load balancing and the other for a proactive measure in failure. Both need machine learning models that learn periodic monitoring data of resource usage and logs from servers and VMs/VNFs. We apply the second method to a vEPC (Virtual Evolved Pakcet Core) failure scenario to provide a detailed case study.

• Convergence Security Journal
• /
• v.16 no.7
• /
• pp.159-165
• /
• 2016

Through the NFV (Network Function Virtualization), companies such as network service providers and carriers have sought to dramatically reduce CAPEX / OPEX by improving the speed of new service provisioning and flexibility of network construction through the S/W-based devices provided by NFV. One of the most important considerations for establishing an NFV network to provide dynamic services is to determine how to dynamically allocate resources (VNFs), the basic building blocks of network services, in the right place. In this paper, we analyzed the latest research trends on VNF node, link allocation, and scheduling in nodes that are required to provide arbitrary NS in NFV framework. In this paper, we also propose VNF scheduling problems that should be studied further in RA (Resource Allocation).

• KNOM Review
• /
• v.23 no.2
• /
• pp.1-10
• /
• 2020

Network Function Virtualization (NFV) is a key technology of 5G networks that has the advantage of enabling building and operating networks flexibly. However, NFV can complicate network management because it creates numerous virtual resources that should be managed. In NFV environments, service function chaining (SFC) composed of virtual network functions (VNFs) is widely used to apply a series of network functions to traffic. Therefore, it is required to dynamically allocate the right amount of computing resources or instances to SFC for meeting service requirements. In this paper, we propose Deep Q-Networks (DQN)-based auto-scaling to operate the appropriate number of VNF instances in SFC. The proposed approach not only resizes the number of VNF instances in SFC composed of multi-tier architecture but also selects a tier to be scaled in response to dynamic traffic forwarding through SFC.

• Journal of Digital Contents Society
• /
• v.19 no.4
• /
• pp.837-844
• /
• 2018

Recently, the cloud technology has made dynamical network changes by enabling the construction of a logical network without building a physical network. Despite recent research on the cloud, it is necessary to study security functions for the identification of fake virtual network functions and the encryption of communication between entities. Because the VNFs are open to subscribers and able to implement service directly, which can make them an attack target. In this paper, we propose a virtual public key infrastructure mechanism that detects a fake VNFs and guarantees data security through mutual authentication between VNFs. To evaluate the virtual PKI, we built a management and orchestration environment to test the performance of authentication and key generation for data security. And we test the detection of a distributed denial of service by using several AI algorithms to enhance the security in NFV.

• Journal of information and communication convergence engineering
• /
• v.17 no.3
• /
• pp.185-190
• /
• 2019

The explosive growth of data traffic and services has created cost challenges for networks. Studies have attempted to effectively apply network slicing in fifth generation networks to provide high speed, low latency, and various compatible services. However, in network slicing using mixed-integer linear programming, the operation count increases exponentially with the number of physical servers and virtual network functions (VNFs) to be allocated. Therefore, we propose an efficient slice allocation method based on cluster technology, comprising the following three steps: i) clustering physical servers; ii) selecting an appropriate cluster to allocate a VNF; iii) selecting an appropriate physical server for VNF allocation. Solver runtimes of the existing and proposed methods are compared, under similar settings, with respect to intra-slice isolation. The results show that solver runtime decreases, by approximately 30% on average, with an increase in the number of physical servers within the cluster in the presence of intra-slice isolation.