• ETRI Journal
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• v.41 no.2
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• pp.207-223
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• 2019

Network function virtualization can significantly improve the flexibility and effectiveness of network appliances via a mapping process called service function chaining. However, the failure of any single virtualized network function causes the breakdown of the entire chain, which results in resource wastage, delays, and significant data loss. Redundancy can be used to protect network appliances; however, when failures occur, it may significantly degrade network efficiency. In addition, it is difficult to efficiently map the primary and backups to optimize the management cost and service reliability without violating the capacity, delay, and reliability constraints, which is referred to as the reliability-aware service chaining mapping problem. In this paper, a mixed integer linear programming formulation is provided to address this problem along with a novel online algorithm that adopts the joint protection redundancy model and novel backup selection scheme. The results show that the proposed algorithm can significantly improve the request acceptance ratio and reduce the consumption of physical resources compared to existing backup algorithms.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.8
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• pp.3701-3727
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• 2016

Recently Service Function Chaining (SFC) is promising to innovate the network service mode in modern networks. However, a feasible implementation of SFC is still difficult due to the need to achieve functional equivalence with traditional modes without sacrificing performance or increasing network complexity. In this paper, we present a configurable network service chaining (CNSC) mechanism to provide services for network traffics in a flexible and optimal way. Firstly, we formulate the problem of network service chaining and design an effective service chain construction framework based on integrating software-defined networking (SDN) with network functions virtualization (NFV). Then, we model the service path computation problem as an integer liner optimization problem and propose an algorithm named SPCM to cooperatively combine service function instances with a network utility maximum policy. In the procedure of SPCM, we achieve the service node mapping by defining a service capacity matrix for substrate nodes, and work out the optimal link mapping policies with segment routing. Finally, the simulation results indicate that the average request acceptance ratio and resources utilization ratio can reach above 85% and 75% by our SPCM algorithm, respectively. Upon the prototype system, it is demonstrated that CNSC outperforms other approaches and can provide flexible and scalable network services.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.12
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• pp.1914-1924
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• 2016

In this paper, considering virtualized Evolved Packet Core(vEPC) network for 5G mobile network, we propose architecture for supporting Service Function Chaining(SFC) in 5G mobile network. Using SFC in 5G network, dynamic path configuration and providing network services based on subscriber and traffic information. SFC technology provides logical ordered set of network functions and delivers packet through providing logical path over the physical network. Based on the perspective of 5G core network in distributed manner, we design hierarchical SFC architecture to manage SFC for global path including vEPC and SGi-LAN network, and internal path between virtualized network functions in each cloud. In this paper, we define architecture and call flow for establishing data path using SFC. Finally, we design testbed architecture for real implementation based on open source software.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.6
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• pp.1032-1039
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• 2015

Service function chaining(SFC) defines the creation of network services that consist of an ordered set of service function. A multiple service function instances should be deployed across networks for scalable and fault-tolerant SFC services. Therefore, an incoming flows should be distributed to multiple service function instances appropriately. In this paper, we formulate the flow distribution problem in SFC aiming at minimizing the end-to-end flow latency under resource constraints. Then, we evaluate its optimal solution in a realistic network topology generated by the GT-ITM topology generator. Simulation results reveal that the optimal solution can reduce the total flow latency significantly.

• Information and Communications Magazine
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• v.31 no.9
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• pp.46-51
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• 2014

미래지향적 네트워크 및 서비스 인프라의 구축을 위해 네트워크의 개방화와 가상화에 대한 관심이 높아졌다. 이를 지원하는 기술로서 SDN (Software-defined Networking) 및 NFV(Network Function Virtualisation) 기술이 소개되었다. 특히 트래픽에 따라 필요한 네트워크 기능들을 선택적으로 조합 및 실행하여 하나의 네트워크 서비스를 구현하는 서비스 체이닝(Service Chaining 혹은 Service Function Chaining) 기술이 높은 관심을 받고 있다. 이를 통해 컴포넌트 서비스들로 이루어진 경로를 정의함으로써 네트워크 서비스를 적시에 구성 및 능동적으로 제어할 수 있다. 본 고에서는 서비스 체이닝 기술의 기본 개념및 기능에 대해 간략히 소개하고, 주요 기능의 표준화를 담당하는 IETF SFC WG 의 주요 표준화 이슈에 대한 분석 및 향후 전망을 기술한다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.10
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• pp.4640-4661
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• 2018

To cope with the explosive growth of Internet services, Service Function Chaining (SFC) based on Software-defined Networking (SDN) is an emerging and promising technology that has been suggested to meet this challenge. Determining the placement of Virtual Network Functions (VNFs) and routing paths that optimize the network utilization and resource consumption is a challenging problem, particularly without violating service level agreements (SLAs). This problem is called the optimal SFC placement problem and an Integer Linear Programming (ILP) formulation is provided. A greedy heuristic solution is also provided based on an improved two-step mapping algorithm. The obtained experimental results show that the proposed algorithm can automatically place VNFs at the optimal locations and find the optimal routing paths for each online request. This algorithm can increase the average request acceptance rate by about 17.6% and provide more than 20-fold reduction of the computational complexity compared to the Greedy algorithm. The feasibility of this approach is demonstrated via NetFPGA-10G prototype implementation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.2
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• pp.577-594
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• 2020

Service Function Chaining (SFC) supports services through linking an ordered list of functions. There may be multiple instances of the same function, which provides a challenge to select available instances for all the functions in an SFC and generate a specific Service Function Path (SFP). Aiming to solve the problem of SFP selection, we propose an architecture consisting of distributed SFP algorithm and central control mechanism. Nodes generate distributed routings based on the first function and destination node in each service request. Controller supervises all of the distributed routing tables and modifies paths as required. The architecture is scalable, robust and quickly reacts to failures because of distributed routings. Besides, it enables centralized and direct control of the forwarding behavior with the help of central control mechanism. Simulation results show that distributed routing tables can generate efficient SFP and the average cost is acceptable. Compared with other algorithms, our design has a good performance on average cost of paths and load balancing, and the response delay to service requests is much lower.

• KNOM Review
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• v.21 no.2
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• pp.1-9
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• 2018

Network virtualization refers to a technology creating independent virtual network environment on a physical network. Network virtualization technology can share the physical network resources to reduce the cost of establishing the network for each user and enables the network administrator to dynamically change the network configuration according to the purpose. Although the network management can be handled dynamically, the management is manual, and it does not maximize the profit of network virtualization. In this paper, we propose Machine-Learning technology to allow the network to learn by itself and manage its management dynamically. The proposed approach is to dynamically allocate appropriate resources by predicting resource demand of VNF in service function chaining, which is a core and essential problem in virtual network management. Our goal is to predict the resource demand of the VNF and dynamically allocate the appropriate resources to reduce the cost of network operation while preventing service interruption.

• KIISE Transactions on Computing Practices
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• v.23 no.2
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• pp.85-96
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• 2017

IoT-Cloud service, integration of Internet of Things (IoT) and Cloud, is becoming a critical model for realizing creative and futuristic application services. Since IoT machines have little computing capacity, it is effective to attaching public Cloud resources for realizing IoT-Cloud service. Furthermore, utilizing containers and adopting a microservice architecture for developing IoT-Cloud service are useful for effective realization. The quality of microservice based IoT-Cloud service is affected by service function chaining which inter-connects each functions. For example, an issue with some of the functions or a bottleneck of inter-connection can degrade the service quality. To ensure functionality of the entire service, various test procedures considering various service environments are required to improve the service continuously. Hence in this paper, we introduce experimental realization of continuous integration based on DevOps and employ application performance monitoring for Node.js based IoT-Cloud service. Then we discuss its effectiveness.

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