• Journal of Information Processing Systems
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• v.9 no.4
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• pp.651-659
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• 2013

In the Host Identity Protocol (HIP), the existing host-based handover scheme tends to induce large handover delays and packet loss rates. To deal with this problem, we are proposing a network-based handover scheme for HIP in the mobile networks, in which the access routers of the mobile node will establish a handover tunnel and will perform the route optimization for data transmission. We also discuss how to extend the HIP Update message to use the proposed handover scheme. From ns-2 simulations, we can see that the proposed handover scheme can significantly reduce the handover delay and packet losses during handover, as compared to the existing handover schemes.

• 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.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.10a
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• pp.63-66
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• 2007

Everytime a node moves out, the connection makes handover which occurs much latency. In NetLMM(Network based Localized Mobility Management), network supports the mobility management for nodes and it improves handover latency using MIH(Media Independent Handover) service. In this paper, we shall analyse and improve the handover latency with addition of some messages to NetLMM protocol.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.8B
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• pp.1159-1169
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• 2010

This paper introduces the mobility-adaptive QoE provisioning solution. The key is placed on the intelligent selection of access network depending on the QoE criteria classified by the user mobility and the bandwidth demand for service. We further focus on the network-based smart handover scheme using the mobility-adaptive handover decision and the enhanced MIH-FMIP framework. The concept is the network-based calm service and the balance in order to facilitate vertical and seamless handover. In result, it is figured out that our solution improves QoE performance by selecting appropriate access network, repressing handover occurrence, and reducing handover delay as well.

• The Journal of the Korea Contents Association
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• v.9 no.7
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• pp.86-94
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• 2009

We propose a network-based global mobility mechanism between the IP based Access Networks. In the core network, the control message and data transmission were separated for fast location registration. In the local area, by applying the PMIPv6 technology, the network-based mobility was possible. Moreover, when the existing handover scheme compared with the proposed handover scheme, we can see definitely that the handover latency time of the proposed handover scheme has better performance than that of the existing handover scheme.

• Journal of information and communication convergence engineering
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• v.8 no.2
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• pp.168-172
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• 2010

The Network-based handover still has problems such as the transmission delays and the packet losses in the case of macro mobility, though technological advances have been made in the wireless and mobile communication. For end-to-end handover, the link bandwidth has been reduced in the wireless network due to its burst errors and congestion control. To overcome such problems, we propose a new scheme of the macro handover according to the protocol layer. The proposed macro handover is implemented on the network layer to partially substitute wired signaling for wireless signaling, to flexibly employ buffers, and on the transport layer to postpone its retransmission time. We have performed extensive simulation using ns-2 and the result shows that our proposed scheme outperforms the other existing schemes in terms of transmission delay, packet loss, and data transfer rate during the handovers.

• Journal of information and communication convergence engineering
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• v.6 no.3
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• pp.245-248
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• 2008

Everytime a node moves out of its area, the connection to the node encounters a handover which may cause much latency. NetLMM(Network based Localized Mobility Management) supports the mobility management for such nodes and improves handover latency using MIH(Media Independent Handover) function. In this paper, we add some messages to NetLMM procedure to improve handover latency and analyze its effects through a scenario based approach

• Journal of Information Processing Systems
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• v.14 no.3
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• pp.771-789
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• 2018

In heterogeneous wireless networks supporting multi-access services, selecting the best network from among the possible heterogeneous connections and providing seamless service during handover for a higher Quality of Services (QoSs) is a big challenge. Thus, we need an intelligent vertical handover (VHO) decision using suitable network parameters. In the conventional VHOs, various network parameters (i.e., signal strength, bandwidth, dropping probability, monetary cost of service, and power consumption) have been used to measure network status and select the preferred network. Because of various parameter features defined in each wireless/mobile network, the parameter conversion between different networks is required for a handover decision. Therefore, the handover process is highly complex and the selection of parameters is always an issue. In this paper, we present how to maximize network utilization as more than one target network exists during VHO. Also, we show how network parameters can be imbedded into IEEE 802.21-based signaling procedures to provide seamless connectivity during a handover. The network simulation showed that QoS-effective target network selection could be achieved by choosing the suitable parameters from Layers 1 and 2 in each candidate network.

• The Transactions of the Korea Information Processing Society
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• v.7 no.8S
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• pp.2608-2619
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• 2000

This paper proposes the Handover Scheme for the mobile and describes the result of the performance analysis. In the conventional scheme of handover request, the withdrawal of terminal may occur because handover request is performed based on fixed signal level without considering network load and terminal mobility. The proposed scheme offers the minimization of withdrawal and handover blocking probability by means of the handover request of terminal based on the network load and terminal mobility. Conventional handover scheme has the sequential procedure that network performs resource check and path rerouting on the handover by MT(Mobile Terminal). Proposed handover scheme pre-processes the resource check before the handover request by predicting the handover request timo so that handover latency can be reduced. Moreover, path optimization is executed after the completion of handover in order to reduce handover latency. The rdduction of handover latency prevents the dropping of service by minimizing backward handover blocking. In summary, we propose the prediction of handover request time and decision method based on terminal, validating the performance of proposed scheme considering various cases of simulation.

• ETRI Journal
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• v.46 no.2
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• pp.205-217
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• 2024

We propose a bandwidth prediction approach based on deep learning. The approach is intended to accurately predict the bandwidth of various types of mobile networks. We first use a machine learning technique, namely, the gradient boosting algorithm, to recognize the connected mobile network. Second, we apply a handover detection algorithm based on network recognition to account for vertical handover that causes the bandwidth variance. Third, as the communication performance offered by 3G, 4G, and 5G networks varies, we suggest a bidirectional long short-term memory model with time distribution for bandwidth prediction per network. To increase the prediction accuracy, pretraining and fine-tuning are applied for each type of network. We use a dataset collected at University College Cork for network recognition, handover detection, and bandwidth prediction. The performance evaluation indicates that the handover detection algorithm achieves 88.5% accuracy, and the bandwidth prediction model achieves a high accuracy, with a root-mean-square error of only 2.12%.