• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2009년도 추계학술대회
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• pp.1046-1048
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• 2009

협업통신은 다중경로페이딩의 문제를 해결하고 전송전력소모를 감소시키기위한 효과적인 기술이다. 릴레이선택과 전력할당은 협업통신의 성능을 결정하는 중요한 요소이다. 본 논문에서는 센서네트워크에서 네트워크수명 극대화를 위해 새로운 형태의 다중 릴레이선택 방법과 전력할당 알고리즘을 제안한다. 제안하는 릴레이 선택 알고리즘은 채널상태 뿐아니라 각 노드의 잔여전력을 함께 고려함으로써 전송전력을 극소화하고 네트워크의 수명을 증가시킨다. 시뮬레이션결과는 제안된 알고리즘이 기존의 방식에비해 더 긴 네트워크 수명을 갖을 수 있음을 보여준다.

• International Journal of Computer Science & Network Security
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• 제23권7호
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• pp.131-140
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• 2023

Network security situational awareness systems helps in better managing the security concerns of a network, by monitoring for any anomalies in the network connections and recommending remedial actions upon detecting an attack. An Intrusion Detection System helps in identifying the security concerns of a network, by monitoring for any anomalies in the network connections. We have proposed a CRF based IDS system using genetic search feature selection algorithm for network security situational awareness to detect any anomalies in the network. The conditional random fields being discriminative models are capable of directly modeling the conditional probabilities rather than joint probabilities there by achieving better classification accuracy. The genetic search feature selection algorithm is capable of identifying the optimal subset among the features based on the best population of features associated with the target class. The proposed system, when trained and tested on the bench mark NSL-KDD dataset exhibited higher accuracy in identifying an attack and also classifying the attack category.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회 2003년도 추계학술대회 및 정기총회
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• pp.183-186
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• 2003

Customer profitability recognition is easier with CRM enabling technologies and the strategy of firing unprofitable customers prevails in the market. However, in the digital and Internet age, network externality is becoming more important. Therefore, the concern over firing unprofitable customers has increased. Our research is intended to develop strategic guidance for customer selection when firms implement CRM in the market with network externality.

• Nuclear Engineering and Technology
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• 제50권4호
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• pp.599-605
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• 2018

Fault diagnosis depends critically on the selection of sensors monitoring crucial process variables. Boolean network (BN) is composed of nodes and directed edges, where the node state is quantized to the Boolean values of True or False and is determined by the logical functions of the network parameters and the states of other nodes with edges directed to this node. Since BN can describe the fault propagation in a sensor network, it can be applied to propose sensor selection strategy for fault diagnosis. In this article, a sufficient condition for parameter identifiability of BN is first proposed, based on which the sufficient condition for fault identifiability of a sensor network is given. Then, the fault identifiability condition induces a sensor selection strategy for sensor selection. Finally, the theoretical result is applied to the fault diagnosis-oriented sensor selection for a nuclear heating reactor plant, and both the numerical computation and simulation results verify the feasibility of the newly built BN-based sensor selection strategy.

• 전기학회논문지
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• 제60권9호
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• pp.1767-1769
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• 2011

In a CR (cognitive radio) network, channel selection is one of the important issues for the efficient channel utilization. When the CR user exploits the spectrum of primary network, the interference to the primary network should be minimized. In this paper, we propose a spectrum hole prediction based channel selection scheme to minimize the interference to the primary network. To predict spectrum hole, statistic properties of primary user's traffic is used. By using the predicted spectrum hole, channel is selected and it can reduce the possibility of interference to the primary user and increase the efficiency of spectrum utilization. The performance of proposed channel selection scheme is evaluated by the computer simulation.

• 한국항행학회논문지
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• 제15권1호
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• pp.76-82
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• 2011

다수의 이종 무선망들 중에서 스케일러블 비디오 스트리밍 서비스에 적합한 망을 선택하는 경우, 기존에는 망 품질만을 고려하였다. 그러나 사용자 중심의 체감품질을 고려하지 않고 망 선택을 함에 따라 서비스에 대한 체감 만족이 낮아지는 문제가 있다. 이에 따라, 본 논문에서는 스케일러블 비디오 스트리밍 서비스를 위해 망의 품질뿐만 아니라 일반 사용자, 가격민감 사용자, 품질민감 사용자로 사용자의 소비성향을 구분하고 비디오 품질열화에 대한 서비스 가격 만족도 등을 고려한 체감품질기반의 망 선택 알고리즘을 제안한다. 실험결과 일반 사용자보다 가격민감 사용자와 품질민감 사용자는 각각 36%, 9% 정도 체감만족 향상을 갖는 망을 선택할 수 있었다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권9호
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• pp.4398-4417
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• 2017

Multi-user Multiple-Input and Multiple-Output (MU-MIMO) has potential for prominently enhancing the capacity of wireless network by simultaneously transmitting to multiple users. User selection is an unavoidable problem which bottlenecks the gain of MU-MIMO to a great extent. Major state-of-the-art works are focusing on improving network throughput by using Channel State Information (CSI), however, the overhead of CSI feedback becomes unacceptable when the number of users is large. Some work does well in balancing tradeoff between complexity and achievable throughput but is lack of consideration of fairness. Current works universally ignore the rational utilizing of time resources, which may lead the improvements of network throughput to a standstill. In this paper, we propose TOUSE, a scalable and fair user selection scheme for MU-MIMO. The core design is dynamic-time-warping-based user selection mechanism for downlink MU-MIMO, which could make full use of concurrent transmitting time. TOUSE also presents a novel data-rate estimation method without any CSI feedback, providing supports for user selections. Simulation result shows that TOUSE significantly outperforms traditional contention-based user selection schemes in both throughput and fairness in an indoor condition.

• 한국통신학회논문지
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• 제36권2A호
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• pp.139-148
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• 2011

본 논문은 멀티밴드 해양통신망에서 선적 정보를 주기적으로 전송할 때 발생하는 비용을 최소화하기 위해 가용한 네트워크의 전송 비용과 주어진 허용 가능한 최대 지연 범위 이내에서 예상되는 최소 평균 전송 비용을 비교하여 전송 시점을 결정하는 방안을 제시한다. 이때 전송 시점과 해당 네트워크의 선택 과정을 Markov Decision Process (MDP)로 모델링하며, 이에 따라 각 밴드에서의 채널 상태를 2-State Markov Chain으로 모델링하고 평균 전송 비용을 Stochastic Dynamic Programming을 통해 계산한다. 이를 통해 최소 비용의 망 선택 방식이 도출되었으며, 제안된 방식을 사용할 때 고정 주기를 사용하여 정보를 전송하는 방식에 비해 상당한 망 사용 비용을 절감할 수 있음을 컴퓨터 시뮬레이션을 통해 보인다.

• Journal of Electrical Engineering and Technology
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• 제13권4호
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• pp.1724-1731
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• 2018

The conventional polynomial neural network (PNN) is a classical flexible neural structure and self-organizing network, however it is not free from the limitation of overfitting problem. In this study, we propose a space search-optimized polynomial neural network (ssPNN) structure to alleviate this problem. Ranking selection is realized by means of ranking selection-based performance index (RS_PI) which is combined with conventional performance index (PI) and coefficients based performance index (CPI) (viz. the sum of squared coefficient). Unlike the conventional PNN, L2-norm regularization method for estimating the polynomial coefficients is also used when designing the ssPNN. Furthermore, space search optimization (SSO) is exploited here to optimize the parameters of ssPNN (viz. the number of input variables, which variables will be selected as input variables, and the type of polynomial). Experimental results show that the proposed ranking selection-based polynomial neural network gives rise to better performance in comparison with the neuron fuzzy models reported in the literatures.

• Journal of Communications and Networks
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• 제17권3호
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• pp.306-320
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• 2015

Due to an explosive growth in services running in different datacenters, there is need for service selection and routing to deliver user requests to the best service instance. In current solutions, it is generally the client that must first select a datacenter to forward the request to before an internal load-balancer of the selected datacenter can select the optimal instance. An optimal selection requires knowledge of both network and server characteristics, making clients less suitable to make this decision. Information-Centric Networking (ICN) research solved a similar selection problem for static data retrieval by integrating content delivery as a native network feature. We address the selection problem for services by extending the ICN-principles for services. In this paper we present Queue and Latency, a network-driven service selection algorithm which maps user demand to service instances, taking into account both network and server metrics. To reduce the size of service router forwarding tables, we present a statistical method to approximate an optimal load distribution with minimized router state required. Simulation results show that our statistical routing approach approximates the average system response time of source-based routing with minimized state in forwarding tables.