• 한국정보과학회논문지:정보통신
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• 제36권3호
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• pp.163-172
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• 2009

다중 인터페이스를 가지는 단말들이 다양한 이기종 무선 네트워크 서비스를 사용할 때 사용자의 버티컬 핸드오버가 증가하게 되었고, 이로 인한 네트워크 자원의 통합적인 관리 문제가 대두되고 있다. 이는 이기종 네트워크에서 자원의 통합 관리(Common Radio Resource Management: CRRM)를 통해 효율적으로 해결 될 수 있다. 본 논문에서는 새로운 사용자가 네트워크에 진입할 때 사용자의 요구 사항을 만족하는 네트워크를 선택하는 Integrated Network Selection 알고리즘과 가용자원이 부족하여 새로운 사용자의 요청을 처리할 수 없을 때 기존 사용자를 주변의 네트위크로 버티컬 핸드오버하여 가용자원을 확보하는 Integrated Vertical Handover 알고리즘을 제안하였고, 그 우수성을 시뮬레이션을 통해 검증하였다.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회 1996년도 추계학술대회발표논문집; 고려대학교, 서울; 26 Oct. 1996
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• pp.186-189
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• 1996

In most of the recent research literature, network performance is expressed in terms of network engineering measures such as delay or loss. These performance measures are important to network owners and operators, but it is believed that user preferences should be the primary consideration which drives the resource allocation scheme. A network is only as valuable as its users perceive it to be. Therefore, it is advocated that the users themselves determine relative traffic priorities. This paper describes the role of feedback in network resource allocation, which could be part of a user-oriented framework for network operation and control. Feedback mechanism can also be used to improve the two types of efficiency in the network; network efficiency and economic efficiency.

• KNOM Review
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• 제21권2호
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• pp.1-9
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• 2018

네트워크 가상화 (Network virtualization)는 물리 네트워크상에서 각 사용자 별로 독립된 가상의 네트워크 환경을 생성하는 기술을 지칭한다. 네트워크 가상화 기술은 물리 네트워크 자원을 공유하여 사용자 별로 네트워크를 구축하는 데 필요한 비용을 절감할 수 있으며, 네트워크 관리자가 요구사항에 따라 동적으로 네트워크를 관리할 수 있도록 돕는다. 하지만 동적으로 네트워크 관리를 수행할 수 있다는 장점에도 불구하고, 관리자가 여전히 직접 판단을 내리고 관리 기능을 실행하는 과정은 동일하다. 네트워크 관리 기능 실행 전까지 관리자에 의해 네트워크 상황을 파악하고 결정을 내리는 과정에는 많은 시간이 소요될 수 있기 때문에 네트워크 가상화로 얻을 수 있는 동적 네트워크 관리라는 장점을 최대화 하지 못하고 있다. 본 논문에서는 기계학습 (Machine Learning) 기술을 도입하여 사람의 도움 없이 네트워크가 스스로 학습하여 동적으로 네트워크 관리를 수행하는 방법을 제안한다. 제안하는 방법은 가상 네트워크 관리에서 핵심적이고 필수적인 문제인 자원관리 최적화 문제를 서비스 펑션 체인(Service Function Chaining) 문제로 정의하고, VNF의 자원 수요를 예측하여 적절한 자원을 동적으로 할당해 서비스 중단이 일어나는 것을 방지하면서 네트워크 운용비용을 절감하는 것을 목표로 한다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권9호
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• pp.4197-4219
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• 2017

Cloud computing is a new service to provide dynamic, scalable virtual resource services via the Internet. Cloud market is available to multiple cloud computing resource providers and users communicate with each other and participate in market transactions. However, since cloud computing is facing with more and more security issues, how to complete the allocation process effectively and securely become a problem urgently to be solved. In this paper, we firstly analyze the cloud resource allocation problem and propose a mathematic model based on combinatorial double auction. Secondly, we introduce a trust evaluation mechanism into our model and combine genetic algorithm with simulated annealing algorithm to increase the efficiency and security of cloud service. Finally, by doing the overall simulation, we prove that our model is highly effective in the allocation of cloud resources.

• Journal of Communications and Networks
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• 제15권5호
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• pp.469-475
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• 2013

In this paper, we propose an efficient interference management technique which controls the number of resource blocks (or subcarriers) shared with other cells based on statistical interference levels among cells. The proposed technique tries to maximize average throughput of a femto cell user under a constraint on non-real time control of a femto cell network while guaranteeing a target throughput value of a macro cell user. In our proposed scheme, femto cells opportunistically use resource blocks allocated to other cells if the required average user throughput is not attained with the primarily allocated resource blocks. The proposed method is similar to the underlay approach in cognitive radio systems, but resource block sharing among cells is statistically controlled. For the statistical control, a femto cell sever constructs a table storing average mutual interference among cells and periodically updates the table. This statistical approach fully satisfies the constraint of non-real time control for femto cell networks. Our simulation results show that the proposed scheme achieves higher average femto user throughput than conventional frequency reuse schemes for time varying number of users.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제6권5호
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• pp.1286-1302
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• 2012

In this paper, the resource allocation problem with proportional fairness rate in cognitive OFDM-based wireless network is studied. It aims to maximize the total system throughput subject to constraints that include total transmit power for secondary users, maximum tolerable interferences of primary users, bit error rate, and proportional fairness rate among secondary users. It is a nonlinear optimization problem, for which obtaining the optimal solution is known to be NP-hard. An efficient bio-inspired suboptimal algorithm called immune clonal optimization is proposed to solve the resource allocation problem in two steps. That is, subcarriers are firstly allocated to secondary users assuming equal power assignment and then the power allocation is performed with an improved immune clonal algorithm. Suitable immune operators such as matrix encoding and adaptive mutation are designed for resource allocation problem. Simulation results show that the proposed algorithm achieves near-optimal throughput and more satisfying proportional fairness rate among secondary users with lower computational complexity.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권5호
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• pp.2243-2257
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• 2019

A heterogeneous cellular network (HCN) is useful to increase the spectral and energy efficiency of wireless networks and to reduce the traffic load from the macro cell. The performance of the secondary user equipment (SUE) is affected by interference from the eNodeB (eNB) in a macro cell. To decrease the interference between the macro cell and the small cell, allocating resources properly is essential to an HCN. This study considers the scenario of a software-defined heterogeneous cellular network and performs the resource allocation process. First, we show the system model of HCN and formulate the optimization problem. The optimization problem is a complex process including power and frequency resource allocation, which imposes an extremely high complexity to the HCN. Therefore, a hierarchical resource allocation scheme is proposed, which including subchannel selection and a particle swarm optimization (PSO)-based power allocation algorithm. Simulation results show that the proposed hierarchical scheme is effective in improving the system capacity and energy efficiency.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권7호
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• pp.2568-2588
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• 2021

Shared mesh protection (SMP) protects traffic against failures occurring in a working path, as with linear protection, and allows resource sharing of protection paths with different endpoints. The SMP mechanism coordinates multiple protection paths that require shared resources when failures occur on multiple working paths. When multiple failures occur in SMP networks sharing limited resources, activation can fail because some of the resources in the protection path are already in use. In this case, a node confirming that a resource is not available has the option to wait until the resource is available or to withdraw activation of the protection path. In this study, we recognize that the protection switching time and the number of protected services can be different, depending on which option is used for SMP networks. Moreover, we propose a detailed design for the implementation of SMP by considering options and algorithms that are commonly needed for network nodes. A simulation shows the performance of an SMP system implemented with the proposed design and utilizing two options. The results demonstrate that resource utilization can be increased or protection switching time can be shortened depending on the option selected by the network administrator.

• ETRI Journal
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• 제43권2호
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• pp.232-245
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• 2021

As wireless communication continues to develop in limited frequency resource environments, it is becoming important to identify the state of spectrum utilization and predict the amount needed in future. It is essential to collect reliable information for data analysis. This paper introduces a platform that enables the gathering of the scheduling information of a long-term evolution (LTE) cellular system without connecting to the network. A typical LTE terminal can confirm its assigned resource information using the configuration parameters delivered from a network. However, our platform receives and captures only the LTE signal over the air and then enables the estimation of the data relevant to scheduling for all terminals within an LTE cell. After extracting the control channel signal without loss from all LTE subframes, it detects valid downlink control information using the proposed algorithm, which is based on the error vector magnitude of depatterned symbols. We verify the reliability of the developed platform by comparing it with real data from mobile phones and service operators. The average difference in resource block utilization is only 0.28%.

• 전자통신동향분석
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• 제34권2호
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• pp.92-100
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• 2019

Vast amounts of different service-specific requirements and vertical network slicing in a 5G network increase the complexity, cost of the network management and resource operations for carriers. To solve this problem, 3GPP is working on the standardization of NWDAF to support the automation of the 5G network by utilizing artificial intelligence technologies based on Big Data to improve the efficiency of network management and resource operation. In addition, the ETSI ZSM Industry Specification Group is developing technical standards for the automation of end-to-end network management and service delivery. This document provides an overall survey of the latest standardization issues of the NWDAF in 3GPP and ETSI ZSM for 5G network automation and intelligence.