• The KIPS Transactions:PartC
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• v.11C no.5
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• pp.659-670
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• 2004

Handoff is one of the most important features for the user's mobility in a wireless cellular communication system. It is related to resource reservation at nearby cells. Resource reservation to the new connection point should occur prior to handoff to enable the user to receive the data or services at the new location, at the same level of service as at the previous location. For the efficient resource reservation, mobility prediction has been reported as an effective means to decrease the call dropping probability and to shorten the handoff latency in a wireless cellular environment. A recently proposed algorithm, ZMHB, makes use of the history of the user's positions within the current cell to predict the next cell. But, the prediction of the ZMHB algorithm is found to be 80∼85% accurate for regular and random movements. In this paper, we propose a new improved ZMHB mobility prediction algorithm, which is called Detailed-ZMHB that uses detailed-zone-based tracking of mo-bile users to predict user movements. The effectiveness of the proposed algorithm is then demonstrated through a simulation.

• Journal of KIISE:Information Networking
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• v.29 no.4
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• pp.412-427
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• 2002

This paper proposes a restoration scheme based on mobility learning and prediction in the presence of the failure of mobility databases in mobile communication systems. In mobile communication systems, mobility databases must maintain the current location information of users to provide a fast connection for them. However, the failure of mobility databases may cause some location information to be lost. As a result, without an explicit restoration procedure, incoming calls to users may be rejected. Therefore, an explicit restoration scheme against the failure of mobility databases is needed to guarantee continuous service availability to users. Introducing mobility learning and prediction into the restoration process allows systems to locate users after a failure of mobility databases. In failure-free operations, the movement patterns of users are learned by a Neuro-Fuzzy Inference System (NFIS). After a failure, an inference process of the NFIS is initiated and the users' future location is predicted. This is used to locate lost users after a failure. This proposal differs from previous approaches using checkpoint because it does not need a backup process nor additional storage space to store checkpoint information. In addition, simulations show that our proposal can reduce the cost needed to restore the location records of lost users after a failure when compared to the checkpointing scheme

• Transactions of the Korean Society of Automotive Engineers
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• v.2 no.3
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• pp.105-112
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• 1994

A computer program was developed for the simulation of mobility and tractive performance of tracked off-road vehicles. Input parameters for the simulation involve those characterizing track and power drive line of a vehicle and soil conditions upon which the vehicle operates. The simulation predicts tractive performance in terms of soil thrust and motion resistance of track device and mobility performance in terms of the maximum speed, time-distance and time-speed relation that a vehicle can obtain under the given soil conditions. It also determines whether or not the vehicle can move in those conditions. An example of performing simulation was presented and its results showed that the performance prediction was reasonably in a good agreement with the published data.

• International journal of advanced smart convergence
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• v.8 no.2
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• pp.39-46
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• 2019

Human mobility estimation plays a key factor in a lot of promising applications including location-based recommendation systems, urban planning, and disease outbreak control. We study the human mobility estimation problem in the case where recent locations of a person-of-interest are unknown. Since matrix decomposition is used to perform latent semantic analysis of multi-dimensional data, we propose a human location estimation algorithm based on matrix factorization to reconstruct the human movement patterns through the use of information of persons with correlated movements. Specifically, the optimization problem which minimizes the difference between the reconstructed and actual movement data is first formulated. Then, the gradient descent algorithm is applied to adjust parameters which contribute to reconstructed mobility data. The experiment results show that the proposed framework can be used for the prediction of human location and achieves higher predictive accuracy than a baseline model.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.9
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• pp.2101-2119
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• 2013

The spectrum allocation is an attractive issue for mobile cognitive radio (CR) network. However, the time-varying characteristic of the spectrum allocation is not fully investigated. Thus, this paper originally deduces the probabilities of spectrum availability and interference constrain in theory under the mobile environment. Then, we propose a prediction mechanism of the time-varying available spectrum lists and the dynamic interference topologies. By considering the node mobility and primary users' (PUs') activity, the mechanism is capable of overcoming the static shortcomings of traditional model. Based on the mechanism, two prediction-based spectrum allocation algorithms, prediction greedy algorithm (PGA) and prediction fairness algorithm (PFA), are presented to enhance the spectrum utilization and improve the fairness. Moreover, new utility functions are redefined to measure the effectiveness of different schemes in the mobile CR network. Simulation results show that PGA gets more average effective spectrums than the traditional schemes, when the mean idle time of PUs is high. And PFA could achieve good system fairness performance, especially when the speeds of cognitive nodes are high.

• Journal of Korean Institute of Industrial Engineers
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• v.34 no.2
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• pp.160-171
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• 2008

MU's mobility patterns can be found from a movement history data. The prediction accuracy and model complexity depend on the degree of application of history data. The more data we use, the more accurate the prediction is. As a result, the location management cost is reduced, but complexity of the model increases. In this paper, we classify MU's mobility patterns into four types. For each type, we find the respective optimal number of application of history data, and predictive location area by using the simulation. The optimal numbers of four types are shown to be different. When we use more than three application of history data, the simulation time and data storage are shown to increase very steeply.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2007.11a
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• pp.388-394
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• 2007

In wireless network, we propose a predictive location update scheme which considers mobile user's(MU's) mobility patterns. MU's mobility patterns can be found from a movement history data. The prediction accuracy and model complexity depend on the degree of application of history data. The more data we use, the more accurate the prediction is. As a result, the location management cost is reduced, but complexity of the model increases. In this paper, we classify MU's mobility patterns into four types. For each type, we find the respective optimal number of application of history data, and predictive location area by using the simulation. The optimal numbers of four types are shown to be different. When we use more than three application of history data, the simulation time and data storage are shown to increase very steeply.

• Journal of KSNVE
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• v.2 no.4
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• pp.273-280
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• 1992

The prediction of vibration response of floor is necessary in order to check whether the floor vibration level will satisfy the allowable vibration standard of precise machinery such as electronic microscopes in semiconductor manufacturing plant before the installation of various neighboring equipment facility. In conventional vibration isolation, we were mainly interested in minimization of vibration transmissibility and stabilization of vibration isolation system. But in order to predict vibration response of floor, it is necessary to know exciting force of equipment installed on the floor and the mobility of the floor. We measured the exciting force of the dropped mass assumed as equipment and the mobility of some practical building floor using large impact hammer. And from this we predicted the vibration response of floor on which the mass dropped. This predicted vibration response of floor is compared with measured vibration response. Through upper procedure, we examined the possibility of predicting vibration response of floor from the information of exciting force of equipment and the mobility of floor.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.5A
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• pp.536-541
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• 2008

This paper proposes a mobility prediction algorithm for the effective handover among hybrid networks. The proposed algorithm is consisted of two mechanisms to predict a mobile terminal's path. First, the mobile terminal will be checking its received signal power level. Then the mobile terminal will judge its path in some network. Second, if the mobile terminal change its path suddenly, it will be dealing with this situation appropriately using the mobile terminal's speed. This paper introduces existing researches and the proposed algorithm. Finally, our algorithm is compared with existing approaches in terms of the handover delay by using the network simulator OPNet version 10.0.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.1B
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• pp.39-49
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• 2012

With group mobility, minimizing routing overhead among intra-group nodes can be achieved by making longer the routing update period, which may lead to degradation of inter-group's routing performance and consequently the inter-group packet delivery success ratio will be decreased. To reduce the inter-group routing overhead without lowering the inter-group packet delivery success ratio, a mobility-adaptive routing update(MARU) scheme is proposed in this paper. Main idea of the proposed scheme is group-based mobility prediction and updating routing paths by selecting intermediate common relay groups.