• Convergence Security Journal
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• v.14 no.7
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• pp.45-51
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• 2014

The most important point in the QoS management system to ensure the quality of the IoT system design goal is quality measurement system and the quality evaluation system. This research study is a matrix model for the IoT based on key quality measures by diagnosis system structure and function. Developing for the quality metrics measured Internet of Things environment will provide the foundation for the Internet of Things quality measurement/analysis. IoT matrix system for quality evaluation is a method to describe the functional requirements and the quality requirements in a single unified table for quality estimation performed. Comprehensive functional requirements and quality requirements by assessing the association can improve the reliability and usability evaluation. When applying the proposed method IoT quality can be improved while reducing the QoS signaling, the processing, the basis for more efficient quality assurances as a whole.

• International journal of advanced smart convergence
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• v.3 no.2
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• pp.18-21
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• 2014

A control application requirements currently used is very low, such as packet loss rate, minimum delay on sensor networks with quality of service (QoS) requirements some packet delivery guarantee. This paper is the sampling period at the end of the actuator and sensor data transfer related to the Miss ratio for each source sensor node, use the controller and the internal ANFIS. The proposed scheme has the advantages of simplicity, scalability, and General. Simulation results of the proposed scheme can provide QoS support in WSANs.

• Proceedings of the Korea Information Processing Society Conference
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• 2010.04a
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• pp.717-720
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• 2010

This paper considers the Quality of Service (QoS) provisioning mechanisms for the WDM burst switched ring networks. The loss-sensitive service and the delay-sensitive service are discussed. Considering their different requirements, different QoS provisioning schemes are proposed to provision them respectively. The proposed schemes are evaluated through simulation results.

• The Transactions of the Korea Information Processing Society
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• v.6 no.11S
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• pp.3229-3242
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• 1999

At recent, the Internet is evolving into the directions which is capable of incorporating stream-type services such as voice and video services due to the remarkable growth of WWW service and the development of new multimedia application services. However, the existing Internet can only support a best-effort delivery model and thus it is difficult to satisfy these requirements as well as to provide the QoS beyond a certain degree. Accordingly, it is imperative to develop QoS-based routing algorithm in order to allow flexible routing by the Internet user's QoS demand and to be applied into wide area networks. In this paper, we presented new routing algorithms for next generation Internet services and made performance evaluations. The proposed algorithms allow the routing by the user's QoS demand level in order to provide the diverse Internet application services based on ATM network environment that is expected to play a role as an infrastructure of next Generation Internet Services.

• Proceedings of the IEEK Conference
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• 2005.11a
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• pp.57-60
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• 2005

In this paper, a dynamic priority-based QoS (DPQoS) provision scheme is proposed for the required QoS from one end of the network to the other in wireless mobile networks. The DPQoS model is used to meet diversity multimedia traffic requirements. This model is come up with a framework for the wireless network of which consists of a core-IP network and also a number of wireless access networks. For the true end-to-end QoS, it is required that the core network is able to support the required QoS for the wireless users. This paper shows a solution to optimize the performance for different traffic classes according to the traffic characteristics. The performance of the proposed scheme is evaluated at delay aspects such as delay and throughput.

• Journal of Korea Society of Industrial Information Systems
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• v.7 no.5
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• pp.103-111
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• 2002

Historically, IP-based internets have been able to provide a simple best-effort delivery service to all applications they carry. Best effort treats all packets equally, with no service level, packet loss, and delay. The best-effort style has generally worked fine. But the needs of users have changed. The want to use the new real-time, multimedia, and multicasting applications. Thus, there is a strong need to be able to support a variety of traffic with a variety of quality-of-service requirements, within the TCP/IP architecture. This paper propose a framework that offers QoS in a DS domain using dynamic node setting method.

• The Journal of the Korea Contents Association
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• v.12 no.4
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• pp.69-75
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• 2012

In this paper, to provide various services of QoS, and moreover applying traffic ratio to CAC(Call Admission Control) algorithm tested how long average data rate and the average packet delay time. When CAC algorithm is not applied, traffic mixture ratio is 1:1:4:4, the FTP Service 0.4, web services 0.6, streaming service 0.7, the packet delay requirements are not satisfied. On the other hand CAC Algorithm is applied, all the service of packet delay are satisfied with arrival rate. Therefore, we can make sure that applying of CAC of traffic control WWW, FTP, Video, VoIP can guarantee the various services of QoS.

• Proceedings of the Korea Society of Information Technology Applications Conference
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• 2002.11a
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• pp.400-406
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• 2002

Historically, IP-based internets have been able to provide a simple best-effort delivery service to all applications they carry. Best effort treats all packets equally, with no service level, packet loss, and delay. The best-effort style has generally worked fine. But the needs of users have changed. The want to use the new real-time, multimedia, and multicasting applications. Thus, there is a strong need to be able to support a variety of traffic with a variety of quality-of-service requirements, within the TCP/IP architecture. This paper propose a framework that offers QoS in a DS domain using dynamic node setting method.

• Journal of IKEEE
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• v.27 no.4
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• pp.379-385
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• 2023

Distributed congestion control (DCC) is a technology that mitigates channel congestion and improves communication performance in high-density vehicular networks. Traditional DCC techniques operate to reduce channel congestion without considering quality of service (QoS) requirements. Such design of DCC algorithms can lead to excessive DCC actions, potentially degrading other aspects of QoS. To address this issue, we propose a deep reinforcement learning-based QoS-adaptive DCC algorithm. The simulation was conducted using a quasi-real environment simulator, generating dynamic vehicular densities for evaluation. The simulation results indicate that our proposed DCC algorithm achieves results closer to the targeted QoS compared to existing DCC algorithms.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.12B
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• pp.1749-1757
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• 2010

This paper considers the cost minimization problem to satisfy QoS (Quality of Service) requirements for a given network, in particular when communication resources to each link can be additionally assigned. For the purpose of quantifying QoS requirements such as data transfer delay and packet loss, we introduce the cost function considering both the link utilization factor and the additionally assigned resource. To minimize this cost function, we firstly formulate a Basic Capacity Planning (BCP) problem, a special case of Network Utility Maximization (NUM). We show that the solution of this BCP problem cannot be optimal via a counter example. In this paper, we suggest the cross-layer design of both additionally assigned resource and routing path, whose initial values are set to the result of BCP problem. This cross-layer design is based on a heuristic approach which presents an effective way to plan how much communication resources should be added to support the QoS requirements in future. By simulation study, we investigate the convergence of the cost function in a more general network topology as well as in a given simple topology.