• ETRI Journal
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• v.29 no.1
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• pp.18-26
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• 2007

This paper presents an improved redundant picture coding method that efficiently enhances the error resiliency of H.264. The proposed method applies polyphase downsampling to residual blocks obtained from inter prediction and selectively encodes the rearranged residual blocks in the redundant picture coding process. Moreover, a spatial-temporal sample construction method is developed for the redundant coded picture, which further improves the reconstructed picture quality in error prone environments. Simulations based on JM11.0 were run to verify the proposed method on different test sequences in various error prone environments with average packet loss rates of 3%, 5%, 10%, and 20%. Results of the simulations show that the presented method significantly improves the robustness of H.264 to packet loss by 1.6 dB PSNR on average over the conventional redundant picture coding method.

• Journal of Information Processing Systems
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• v.20 no.1
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• pp.131-147
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• 2024

A routing strategy based on traffic prediction and dynamic cache allocation for satellite nodes is proposed to address the issues of high propagation delay and overall delay of inter-satellite and satellite-to-ground links in low Earth orbit (LEO) satellite systems. The spatial and temporal correlations of satellite network traffic were analyzed, and the relevant traffic through the target satellite was extracted as raw input for traffic prediction. An improved gradient boosting regression tree algorithm was used for traffic prediction. Based on the traffic prediction results, a dynamic cache allocation routing strategy is proposed. The satellite nodes periodically monitor the traffic load on inter-satellite links (ISLs) and dynamically allocate cache resources for each ISL with neighboring nodes. Simulation results demonstrate that the proposed routing strategy effectively reduces packet loss rate and average end-to-end delay and improves the distribution of services across the entire network.

• ETRI Journal
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• v.22 no.4
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• pp.40-50
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• 2000

We apply a "sliding-window" Maximum Likelihood(ML) estimator to estimate traffic parameters On-Off source and develop a method for estimating stochastic predicted individual cell arrival rates. Based on these results, we propose a simple Connection Admission Control(CAC)scheme for delay sensitive services in broadband onboard packet switching satellite systems. The algorithms are motivated by the limited onboard satellite buffer, the large propagation delay, and low computational capabilities inherent in satellite communication systems. We develop an algorithm using the predicted individual cell loss ratio instead of using steady state cell loss ratios. We demonstrate the CAC benefits of this approach over using steady state cell loss ratios as well as predicted total cell loss ratios. We also derive the predictive saturation probability and the predictive cell loss ratio and use them to control the total number of connections. Predictive congestion control mechanisms allow a satellite network to operate in the optimum region of low delay and high throughput. This is different from the traditional reactive congestion control mechanism that allows the network to recover from the congested state. Numerical and simulation results obtained suggest that the proposed predictive scheme is a promising approach for real time CAC.

• Journal of the Korea Computer Industry Society
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• v.3 no.1
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• pp.95-104
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• 2002

This paper presents some studies on the Internet TCP/IP(Transmission Control Protocol-Internet Protocol) traffic over ATM(Asynchronous Transfer Mode) UBR(Unspecified Bit Rate) and ABR(Available Bit Rate) classes of service. Fuzzy logic prediction has been used to improve the efficiency and fairness of traffic throughput. For TCP/IP over UBR, a novel fuzzy logic based cell dropping scheme is presented. This is referred to as fuzzy logic selective cell drop (FSCD). A key feature of the scheme is its ability to accept or drop a new incoming packet dynamically based on the predicted future buffer condition in the switch. This is achieved by using fuzzy logic prediction for the production of a drop factor. Packet dropping decision is then based on this drop factor and a predefined threshold value. Simulation results show that the proposed scheme significantly improves TCP/IP efficiency and fairness. To study TCP/IP over ABR, we applied the fuzzy logic ABR service buffer management scheme from our previous work to both approximate and exact fair rate computation ER(Explicit cell Rate) switch algorithms. We then compared the performance of the fuzzy logic control with conventional schemes. Simulation results show that on zero TCP packet loss, the fuzzy logic control scheme achieves maximum efficiency and perfect fairness with a smaller buffer size. When mixed with VBR traffic, the fuzzy logic control scheme achieves higher efficiency with lower cell loss.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.43 no.12 s.354
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• pp.53-60
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• 2006

Handover of WiBro is based on 802.16e hard handover scheme. When PSS is handover, it is handover that confirm neighbor's cell condition and RAS ID in neighbor advertisement message. Serving RAS transmits HO-notification message to neighbor RAS. Transmiting HO-notification message to neighbor RAS, it occurs many signaling traffics. Also, When WiBro is handover, It occurs many packet loss. Therefore, user suffer service degradation. LPM handover is supporting seamless handover because it buffers data packets during handover. So It is proposed scheme that predicts is LPM handover and reserves target RAS with pre-authentication. These schemes occur many signaling traffics. In this paper, we propose PSS Movement Prediction to solve signaling traffic. Target RAS is decided by old data in history cache. When serving RAS receives HO-notification-RSP message to target RAS, target RAS inform to crossover node. And crossover node bicast data packet. If handover is over, target RAS forward data packet. Therefore, It reduces signaling traffics but increase handover success rate. When history cache success, It decrease about 48% total traffic. But When history cache fails, It increase about 6% total traffic

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.11C
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• pp.655-661
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• 2011

The transmission issues for the scalable video coding extension of H.264/AVC (H.264 SVC) video has been widely studied. In this paper, we propose an objective video-quality assessment metric based on no-reference for H.264 SVC using scalability information. The proposed metric estimate the perceptual video-quality reflecting error conditions with the consideration of the motion vectors, error propagation patterns with the hierarchical prediction structure, quantization parameters, and number of frame which damaged by packet loss. The proposed metric reflects the human perceptual quality of video and we evaluate the performance of proposed metric by using correlation relationship between differential mean opinion score (DMOS) as a subjective quality and proposed one.

• Journal of KIISE:Information Networking
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• v.37 no.4
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• pp.284-293
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• 2010

For the successful deployment of Mobile Internet, fast handover technologies are essential. For the past few years several handover mechanisms are suggested, and Fast Handover for Proxy Mobile IPv6 (PFMIPv6) is one of the promising schemes for this purpose. In this paper, we propose a novel L2/L3 cross layer handover scheme based on ARIMA prediction model to apply PFMIPv6 to Mobile Internet environment effectively. Performance gains are evaluated in terms of probabilities of predictive-mode operation, handover latencies, packet loss probabilities, and signaling costs. Three mobilities models are used for our simulation: Manhattan Model, Open Area Model, and Freeway Model. Simulation results show that the proposed scheme can increase probabilities of predictive-mode operation and reduce handover latency, packet loss probabilities, and signaling cost.

• Journal of Communications and Networks
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• v.16 no.6
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• pp.645-655
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• 2014

Latency, an identified element of Internet protocol (IP) mobility protocol execution, can reduce handover performance in mobile networks. Although the performance can be improved by applying an effective network-based IP mobility scheme in place of the traditional host-based alternatives, the existing inter-domain extensions of network-based IP mobility continue to suffer from an extended handover latency. This paper proposes a new inter-domain network-based IP mobility scheme based on node movement prediction. The proposed scheme accelerates the handover by preparing the future domain of the mobile node in a proactive manner. Analytical and simulation-based evaluations confirm improved performance of the proposed scheme in terms of handover latency and packet loss compared with existing schemes.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.4
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• pp.385-391
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• 2005

As the Internet real-time multimedia applications increases, the bandwidth available to TCP connections is oppressed by the UDP traffic, result in the performance of overall system is extremely deteriorated. Therefore, developing a new transmission protocol is necessary. The TCP-friendly algorithm is an example satisfying this necessity. The TCP-Friendly Rate Control (TFRC) is an UDP-based protocol that controls the transmission rate that is based on the available round trip time (RTT) and the packet loss rate (PLR). In the data transmission processing, transmission rate is determined based on the conditions of the previous transmission period. If the one-step ahead predicted values of the control factors are available, the performance will be improved significantly. This paper proposes a prediction model of transmission rate control factors that will be used in the transmission rate control, which improves the performance of the networks. The model developed through this research is predicting one-step ahead variables of RTT and PLR. A multiplayer perceptron neural network is used as the prediction model and Levenberg-Marquardt algorithm is used for the training. The values of RTT and PLR were collected using TFRC protocol in the real system. The obtained prediction model is validated using new data set and the results show that the obtained model predicts the factors accurately.

• International Journal of Computer Science & Network Security
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• v.21 no.3
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• pp.229-234
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• 2021

The explosive growth of video-based services is considered as the dominant contributor to Internet traffic. Hence it is very important for video service providers to meet the quality expectations of end-users. In the past, the Quality of Service (QoS) was the key performance of networks but it considers only the network performances (e.g., bandwidth, delay, packet loss rate) which fail to give an indication of the satisfaction of users. Therefore, Quality of Experience (QoE) may allow content servers to be smarter and more efficient. This work is motivated by the inherent relationship between the QoE and the QoS. We present a no-reference (NR) prediction model based on Deep Neural Network (DNN) to predict video QoE. The DNN-based model shows a high correlation between the objective QoE measurement and QoE prediction. The performance of the proposed model was also evaluated and compared with other types of neural network architectures, and three known machine learning methodologies, the performance comparison shows that the proposed model appears as a promising way to solve the problems.