• 인터넷정보학회논문지
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• 제22권5호
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• pp.27-33
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• 2021

With the broad adoption of the Internet of Things (IoT) in a variety of scenarios and application services, management and orchestration entities require upgrading the traditional architecture and develop intelligent models with ultra-reliable methods. In a heterogeneous network environment, mission-critical IoT applications are significant to consider. With erroneous priorities and high failure rates, catastrophic losses in terms of human lives, great business assets, and privacy leakage will occur in emergent scenarios. In this paper, an efficient resource slicing scheme for optimizing federated learning in software-defined IoT (SDIoT) is proposed. The decentralized support vector regression (SVR) based controllers predict the IoT slices via packet inspection data during peak hour central congestion to achieve a time-sensitive condition. In off-peak hour intervals, a centralized deep neural networks (DNN) model is used within computation-intensive aspects on fine-grained slicing and remodified decentralized controller outputs. With known slice and prioritization, federated learning communications iteratively process through the adjusted resources by virtual network functions forwarding graph (VNFFG) descriptor set up in software-defined networking (SDN) and network functions virtualization (NFV) enabled architecture. To demonstrate the theoretical approach, Mininet emulator was conducted to evaluate between reference and proposed schemes by capturing the key Quality of Service (QoS) performance metrics.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권1호
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• pp.1-17
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• 2016

The separated management and operation of commercial IP/optical multilayer networks makes network operators look for a unified control plane (UCP) to reduce their capital and operational expenditure. Software-defined networking (SDN) provides a central control plane with a programmable mechanism, regarded as a promising UCP for future optical networks. The general control and scheduling mechanism in SDN-based optical burst switching (OBS) networks is insufficient so the controller has to process a large number of messages per second, resulting in low network resource utilization. In view of this, this paper presents the burst-flow scheduling mechanism (BFSM) with a proposed scheduling algorithm considering channel usage. The simulation results show that, compared with the general control and scheduling mechanism, BFSM provides higher resource utilization and controller performance for the SDN-based OBS network in terms of burst loss rate, the number of messages to which the controller responds, and the average latency of the controller to process a message.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권2호
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• pp.514-535
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• 2019

Information-centric networks operate under the assumption that all network components have built-in caching capabilities. Integrating the caching strategies of information centric networking (ICN) with wireless virtualization improves the gain of virtual infrastructure content caching. In this paper, we propose a framework for software-defined information centric virtualized wireless device-to-device (D2D) networks. Enabling D2D communications in virtualized ICN increases the spectral efficiency due to reuse and proximity gains while the software-defined network (SDN) as a platform also simplifies the computational overhead. In this framework, we propose a joint virtual resource and cache allocation solution for latency-sensitive applications in the next-generation cellular networks. As the formulated problem is NP-hard, we design low-complexity heuristic algorithms which are intuitive and efficient. In our proposed framework, different services can share a pool of infrastructure items. We evaluate our proposed framework and algorithm through extensive simulations. The results demonstrate significant improvements in terms of visiting latency, end user QoE, InP resource utilization and MVNO utility gain.

• 정보와 통신
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• 제33권6호
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• pp.18-26
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• 2016

Network and network functions virtualization (NFV) promise a number of attractive benefits and thus have driven mobile network operators to transform their previously static networks to more dynamic and software-defined networks. In this article, we share a mobile network operator's view based on implementation and deployment experiences in the wild during the past few years towards a software-defined 5G core network. More specifically, we present a practical point of view from mobile network operators and elaborate on why some of the virtualization benefits such as total cost of ownership (TCO) reduction are not easily realized as initially intended. Then, we describe 5G visions, services, and their requirements commonly agreed across mobile operators globally. Given the requirements, we then introduce desirable characteristics of 5G mobile core network and its key enabling technologies.

• 인터넷정보학회논문지
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• 제23권2호
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• pp.1-7
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• 2022

Machine learning (ML) algorithms have been intended to seamlessly collaborate for enabling intelligent networking in terms of massive service differentiation, prediction, and provides high-accuracy recommendation systems. Mobile edge computing (MEC) servers are located close to the edge networks to overcome the responsibility for massive requests from user devices and perform local service offloading. Moreover, there are required lightweight methods for handling real-time Internet of Things (IoT) communication perspectives, especially for ultra-reliable low-latency communication (URLLC) and optimal resource utilization. To overcome the abovementioned issues, this paper proposed an intelligent scheme for traffic steering based on the integration of MEC and lightweight ML, namely support vector machine (SVM) for effectively routing for lightweight and resource constraint networks. The scheme provides dynamic resource handling for the real-time IoT user systems based on the awareness of obvious network statues. The system evaluations were conducted by utillizing computer software simulations, and the proposed approach is remarkably outperformed the conventional schemes in terms of significant QoS metrics, including communication latency, reliability, and communication throughput.

• ETRI Journal
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• 제40권2호
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• pp.227-236
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• 2018

Ultra-dense small cell networks (UD-SCNs) have been identified as a promising scheme for next-generation wireless networks capable of meeting the ever-increasing demand for higher transmission rates and better quality of service. However, UD-SCNs will inevitably suffer from severe interference among the small cell base stations, which will lower their spectral efficiency. In this paper, we propose a software-defined networking (SDN)-based hierarchical agglomerative clustering (SDN-HAC) framework, which leverages SDN to centrally control all sub-channels in the network, and decides on cluster merging using a similarity criterion based on a suitability function. We evaluate the proposed algorithm through simulation. The obtained results show that the proposed algorithm performs well and improves system payoff by 18.19% and 436.34% when compared with the traditional network architecture algorithms and non-cooperative scenarios, respectively.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권7호
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• pp.2936-2951
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• 2016

An emerging satellite technology, Operationally Responsive Space (ORS) is expected to provide a fast and flexible solution for emergency response, such as target tracking, dense earth observation, communicate relaying and so on. To realize large distance transmission, we propose the use of available relay satellites as relay nodes. Accordingly, we apply software defined network (SDN) technology to ORS networks. We additionally propose a satellite network architecture refered to as the SDN-based ORS-Satellite (Sat) networking scheme (SDOS). To overcome the issures of node failures and dynamic topology changes of satellite networks, we combine centralized and distributed routing mechanisms and propose a fast recovery routing algorithm (FRA) for SDOS. In this routing method, we use centralized routing as the base mode.The distributed opportunistic routing starts when node failures or congestion occur. The performance of the proposed routing method was validated through extensive computer simulations.The results demonstrate that the method is effective in terms of resoving low end-to-end delay, jitter and packet drops.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권7호
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• pp.3671-3689
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• 2019

Software defined networking brings unique security risks such as control plane saturation attack while enhancing the performance of wireless sensor networks. The attack is a new type of distributed denial of service (DDoS) attack, which is easy to launch. However, it is difficult to detect and hard to defend. In response to this, the attack threat model is discussed firstly, and then a DDoS attack prevention extension, called FuzzyGuard, is proposed. In FuzzyGuard, a control network with both the protection of data flow and the convergence of attack flow is constructed in the data plane by using the idea of independent routing control flow. Then, the attack detection is implemented by fuzzy inference method to output the current security state of the network. Different probabilistic suppression modes are adopted subsequently to deal with the attack flow to cost-effectively reduce the impact of the attack on the network. The prototype is implemented on SDN-WISE and the simulation experiment is carried out. The evaluation results show that FuzzyGuard could effectively protect the normal forwarding of data flow in the attacked state and has a good defensive effect on the control plane saturation attack with lower resource requirements.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권11호
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• pp.3523-3543
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• 2022

Autonomous vehicles are gradually being regarded as the mainstream trend of future development of the automobile industry. Autonomous driving networks generate many intensive and delay-sensitive computing tasks. The storage space, computing power, and battery capacity of autonomous vehicle terminals cannot meet the resource requirements of the tasks. In this paper, we focus on the task scheduling problem of autonomous driving in software-defined edge networks. By analyzing the intensive and delay-sensitive computing tasks of autonomous vehicles, we propose an emotion model that is related to task urgency and changes with execution time and propose an optimal base station (BS) task scheduling (OBSTS) algorithm. Task sentiment is an important factor that changes with the length of time that computing tasks with different urgency levels remain in the queue. The algorithm uses task sentiment as a performance indicator to measure task scheduling. Experimental results show that the OBSTS algorithm can more effectively meet the intensive and delay-sensitive requirements of vehicle terminals for network resources and improve user service experience.

• 한국융합학회논문지
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• 제8권8호
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• pp.51-57
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• 2017

무선 센서 네트워크는 자원 제약적인 센서 노드들로 구성되는 네트워크로, 분산 서비스 거부 공격, 라우팅 공격 등 다양한 악의적인 공격이 발생될 수 있다. 본 논문에서는 소프트웨어 정의 네트워킹 기술과 보안 기술을 융합하여 무선 센서 네트워크에 발생하는 다양한 공격을 탐지하고 방어하는 기법을 제안한다. 제안 기법에서는 서버에 있는 침입 탐지 및 방지 시스템이 SDN 컨트롤러를 통해 전달되는 오픈플로우 스위치의 로그 정보들을 축적하여 침입을 탐지하며, 침입을 탐지했을 때 오픈플로우 프로토콜을 이용하여 오픈플로우 스위치에 해당 침입에 대한 대응방안을 설정함으로써 침입을 방지할 수 있다. 본 논문에서는 분산 서비스 거부 공격 및 라우팅 공격 발생 시 침입 탐지 및 방지를 보임으로써 제안기법의 타당성을 보였다. 제안기법은 다른 기법과 달리 중앙 집중 서버에서 그래프 모델과 침입 탐지 모델을 융합하여 효과적이고 메시지 효율적으로 다양한 침입을 탐지하고 방지할 수 있다.