• Journal of Advanced Navigation Technology
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• v.18 no.5
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• pp.415-420
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• 2014

Another crucial issue is a providing secondary user(SU) with the its guaranteed quality of service(QoS) in cognitive radio systems, from the SU view to be allowed to opportunistically utilize the primary user(PU) spectrum on non-interfering. In this paper, we propose a bandwidth reallocation scheme for reducing SU dropping rate through renegotiation of requested channel numbers when available bandwidth is not enough for accepting the spectrum handoff SUs. We categorize SU calls into two types : the first priority and the second priority SU, and the first SU' service is supported by bandwidth reservation based on ARMA prediction model for PU arrivals, while the second SU's bandwidth demands for spectrum handoff is to be reallocated through their renegotiation. Simulation results show that our scheme can improve SU dropping rate and system resource utilization efficiency by bandwidth reallocation.

• Journal of Advanced Navigation Technology
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• v.26 no.4
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• pp.219-225
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• 2022

In this paper, we propose a CAC exploring a RA based dynamic spectrum hole grouping for secondary users' QoS enhancement in multi-classes cognitive radio networks. The RA based dynamic spectrum hole grouping uses SU multi-classes overlaying spectrum structure suggested here. Multiclass SUs are divided into real and non real, and real SUs have a priority for resource utilization against non real. The amount of resource required by real SUs is supported by Wiener prediction and the dynamic spectrum hole grouping, and that required by non real SU is supported by the remained available amount without prediction. In the simulations, we compare the proposed CAC performances using the dynamic spectrum hole grouping in terms of SU connection's blocking(dropping) rate and resource utilization efficiency according to multi-classes traffic characteristics, and then we show the proposed CAC can guarantee the desired QoS of multi-classes secondary users.

• Journal of Advanced Navigation Technology
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• v.17 no.4
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• pp.435-441
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• 2013

This paper proposes a neural net based-predictive connection admission control (CAC) scheme for multiclass users in wireless cognitive radio networks. We classifies cognitive users(cu) into real and non real time services, and then permit only real time services to reserve the demanded resource for spectrum handoff in guard channel for provisioning the desired QoS. Neural net is employed to predict primary user's arrival on time and demanded channels. Resource scheduling scheme is based on $C_IA$(cognitive user I complete access) shown in this paper. For keeping primary users from interference, the CAC is performed on only cognitive user not primary user. Simulation results show that our schemes can guarantee the desired QoS by cognitive real time services.

• Journal of Advanced Navigation Technology
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• v.19 no.4
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• pp.318-322
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• 2015

In wireless communication networks, most of the prediction techniques are used for predicting the amount of resource required by user's calls for improving their demanding quality of service. However, we propose a channel allocation scheme based on predicting the resources of white spectrum holes for improving the QoS of rental user's spectrum handoff calls for cognitive radio networks in this paper. This method is supported by Wiener predictor to predict the amount of white spectrum holes of license user's free spectrum resources. We classify rental user's calls into initial calls and spectrum handoff calls, and some portion of predicted spectrum-hole resources is reserved for spectrum handoff calls' priority allocation. Simulations show that the performance of the proposed scheme outperforms in spectrum handoff call's dropping rate than an existing method without spectrum hole prediction(11% average improvement in 50% reservation).

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.9B
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• pp.829-837
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• 2006

Due to the internet network congestion, packets may be dropped or delayed at routers. This phenomenon degrades the quality of streaming applications that require high QoS requirements. The proposed algorithm in this paper, called DBRC(Delay-Based Rate Control), tries to cause router queue occupancy to reach a steady state or equilibrium by throttling the transmission rate of the multimedia traffics when network delays tend to increase and also probing for more bandwidth when network delays tend to decrease. Simulation results show that the proposed algorithm provides smooth transmission rate, nearly constant delay and low packet loss rates, compared with TFRC(TCP Friendly Rate Control) that is one of dominant multimedia congestion control algorithms.

• Journal of KIISE:Information Networking
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• v.30 no.1
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• pp.65-74
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• 2003

In this Paper, we propose a downlink service admission strategy that considers users QoS requirements by using a novel service quality prediction index for multi-service WCDMA mobile systems. The Proposed downlink service admission strategy is obtained by computing average received Power of each service, assuming a relative other-cell interference factor. With the proposed method we obtain a downlink service admission region where users of different services properly can be admitted. And adding the fairness at the proposed downiinh service admission strategy, we Propose another downlink service admission strategy. In the numerical examples, the downlink service admission region with fairness and the downlink service admission region without fairness of voice service and data services are obtained by proposed downlink service admission strategies, respectively.

• Annual Conference of KIPS
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• 2015.10a
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• pp.983-986
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• 2015

물리적, 논리적 공간에서 다양한 오브젝트들이 상호작용할 수 있게 되고, 오브젝트에 탑재되는 소프트웨어가 고도화 됨에 따라 엔지니어가 관리 가능한 수준의 시스템 제어가 힘들어지고 있다. 이런 복잡한 시스템의 자율적인 관리를 위해 다양한 상황에 대응 가능한 자가적응성이 요구된다. 자가적응형 소프트웨어는 대상 시스템의 목표나 QoS를 만족할 수 있도록 런타임에 스스로를 변화 시킬 수 있는 능력을 가진 소프트웨어이다. 이러한 소프트웨어는 고도화된 시스템의 관리에 있어서 엔지니어의 부담을 경감시킬수 있다. 본 논문에서 제안하는 선행적 자가적응형 시스템은 도로망과 같은 주기적 특성을 가진 시스템에서 시스템이 직면하는 상황을 사전에 예측하여 미리 대응할 수 있는 시스템이다. 이는 기존에 반응적으로 대응했던 시스템들이 적용한 정책의 효과를 보기까지 낭비되는 시간을 고려하여 해당 지연시간동안에 시스템의 목표나 QoS가 하락하는 상황을 미연에 방지할 수 있다. 본 시스템의 적용분야로 지능형교통체계를 사용하였으며, 도로망 전체에서 정체 발생빈도와 평균 이동속도 그리고 단위길이당 운행시간을 평가항목으로 사용하고, 대상 도로망 전체적인 최적화를 목표로 한다.

• 전자공학회논문지 IE
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• v.45 no.1
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• pp.15-23
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• 2008

In this paper, an algorithm, that provisions absolute differentiation of packet delays is proposed, simulated, and implemented with VHDL on XPC 860 CPU based test board with an objective for enhancing quality of service (QoS) in future packet networks. It features a scheme that compensates the deviation for prediction on the traffic to be arrived continuously. It predicts the traffic to be arrived at the beginning of a time slot and measures the actual arrived traffic at the end of the time slot and derives the difference between them. The deviation is utilized to the delay control operation for the next time slot to offset it. As it compensates the prediction error continuously, it shows superior adaptability to the bursty traffic as well as the exponential traffic. It is demonstrated through both simulation and the real traffic test on the board that the algorithm meets the quantitative delay bounds and shows superiority to the traffic fluctuation in comparison with the conventional non-adaptive mechanism.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.43 no.6 s.348
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• pp.30-38
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• 2006

In this paper, an algerian that provisions absolute and proportional differentiation of packet delays is proposed with an objective for enhancing quality of service (QoS) in future packet networks. It features a scheme that compensates the deviation for prediction on the traffic to be arrived continuously It predicts the traffic to be arrived at the beginning of a time slot and measures the actual arrived traffic at the end of the time slot and derives the difference between them. The deviation is utilized to the delay control operation for the next time slot to offset it. As it compensates the prediction error continuously, it shows superior adaptability to the bursty traffic as well as the exponential traffic. It is demonstrated through simulation that the algorithm meets the quantitative delay bounds and shows superiority to the traffic fluctuation in comparison with the conventional non-adaptive mechanism.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.2B
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• pp.44-52
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• 2005

This paper proposes a neural network prediction model to improve the valid packet transmission rate for the QoS(Quality of Service) of multimedia transmission. The Round Trip Time(RTT) and Packet Loss Rate(PLR) are predicted using a neural network and then the transmission rate is decided based on the predicted RTT and the PLR. The suggested method will improve the transmission rate since it uses the rate control factors corresponding to time of data is being transmitted, while the conventional one uses the transmission rate determined based on the past informations. An experimental set-up has been established using a Linux PC system, and the multimedia data are transmitted using UDP protocol in real time. The valid transmitted packets are about 5% higher than the one in the conventional TCP-Friendly congestion control method when the suggested algorithm was applied.