• Journal of Korea Multimedia Society
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• v.12 no.6
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• pp.824-832
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• 2009

Multi-radio multi-channel Wireless Mesh Network requires an effective management policy to control the assignment of channels to each radio. We concentrated our investigation on modeling method and solution to find a dynamic channel assignment scheme that is adapted to change of network traffic. Multi-path routing scheme was chosen to overwhelm the unreliability of wireless link. For a particular traffic state, our optimization model found a specific traffic distribution over multi-path and a channel assignment scheme that maximizes the overall network throughput. We developed a simple heuristic method for channel assignment by gradually removing clique load to obtain higher throughput. We also presented numerical examples and discussion of our models in comparison with existing research.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.81-82
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• 2006

Most work on cooperative diversity has assumed that the cooperating group (source and partners) and the associated average channel conditions between terminals (source, partners, and destination) are predetermined. In practical situations, however, it is important to develop the efficient algorithms for assigning the terminals with good inter-user channels for cooperating groups. In this paper, we propose the partner assignment algorithm for cooperative diversity in mobile communication systems. The proposed partner assignment algorithm is investigated by using the path loss model for mobile communication systems. Numerical results show that the proposed partner assignment algorithm provides the comparable probability of cooperative transmission to the partner assignment algorithm using exhaustive search. The probability of cooperative transmission increases with the number of users, which gives potential benefits of practical implementation to user cooperation in mobile communication systems.

• Journal of Korean Institute of Industrial Engineers
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• v.18 no.2
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• pp.23-29
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• 1992

To compute the expected travel time of storage and retrieval (S/R) machine in automated warehousing systems most of the previous studies assumed that equal number of rack openings are required regardless of the nature of storage assignment rules. It is known that randomized storage assignment rule usually needs less storage to space than needed for full turnover-based assignment rule. The objective of this paper is compute the expected travel time of each assignment rule more equitably by taking into account the storage space required for each rule. First, the rack storage space is determined which satisfies a given service level. Then based on the standard Economic Ordering Quantity model, trade-off analysis is carried out which relates the storage space to the expected travel time of the S/R machine. Finally, example problems are solved to compare the performance of each assignment rule under varying conditions of demand pattern and service level.

• Journal of Korean Society of Transportation
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• v.25 no.2 s.95
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• pp.133-143
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• 2007

Previous studies on the transit assignment hardly show its achievement in research but have many limitations not only in theory but also in practice. This paper presents an integrated transit assignment model taking into account cost functions of multiple modes, such as auto, bus and subway, which represent an integrated network. An integrated transit network including cost functions and in-vehicle congestion needs to be developed. In addition, a link fare calculation model needs to be developed and applied to the model to calculate path travel costs. Based on these sub-models, a path-based traffic assignment model, which considers in-vehicle congestion and an integrated distance-based fare system in the integrated traffic network, is developed.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.1
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• pp.53-63
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• 2022

In the paper, we propose a TSCH-based scheduling scheme for IEEE 802.15.4e, which is able to perform the scheduling of its own network by avoiding collision from interference network cluster (INC). Firstly, we model a bipartite graph structure for presenting the slot-frame (channel-slot assignment) of TSCH. Then, based on the bipartite graph edge weight, we utilize the Hungarian assignment algorithm to implement a scheduling scheme. We have employed two features (maximization and minimization) of the Hungarian-based assignment algorithm, which can perform the assignment in terms of minimizing the throughput of INC and maximizing the throughput of own network. Further, in this work, we called the scheme "dual-stage Hungarian-based assignment algorithm". Furthermore, we also propose deep learning (DL) based deep neural network (DNN)scheme, where the data were generated by the dual-stage Hungarian-based assignment algorithm. The performance of the DNN scheme is evaluated by simulations. The simulation results prove that the proposed DNN scheme providessimilar performance to the dual-stage Hungarian-based assignment algorithm while providing a low execution time.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2005.10a
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• pp.321-333
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• 2005

With the limited frequency spectrum and an increasing demand for cellular communication services, the problem of channel assignment becomes increasingly important. However, finding a conflict free channel assignment with the minimum channel span is NP hard. As demand for services has expanded in the cellular segment, sever innovations have been made in order to increase the utilization of bandwidth. The innovations are cellular concept, dynamic channel assignment and hierarchical network design. Hierarchical network design holds the public eye because of increasing demand and quality of service to mobile users. We consider the frequency assignment problem and the base station placement simultaneously. Our model takes the candidate locations emanating from this process and the cost of assigning a frequency, operating and maintaining equipment as an input. In addition, we know the avenue and demand as an assumption. We propose the network about the profit maximization. This study can apply to GSM(Global System for Mobile Communication) which has 70% portion in the world. Hierarchical network design using GA(Genetic Algorithm) is the first three-tier (Macro, Micro, Pico) model, We increase the reality through applying to EMC (Electromagnetic Compatibility Constraints). Computational experiments on 72 problem instances which have 15${\sim}$40 candidate locations demonstrate the computational viability of our procedure. The result of experiments increases the reality and covers more than 90% of the demand.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.18 no.3
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• pp.339-347
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• 1993

The channel assignment problem in a mobile communication system is a NP-complete combinatorial optimization problem, in which the calculation time increases exponentially as the range of the problem is extended. This paper adapts a conventional Hopfield neural network model to the channel assignment problem to relieve the calculation time by means of the parallelism supplied from the neural network. In the simulation study, we checked the feasability of such a parallel method for the fixed channel assignment with uniform, and nouniform channel requirements, and for the dynamic channel assignment with considering continously varying channel requirements.

• Journal of the Korean Society for Railway
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• v.17 no.2
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• pp.140-147
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• 2014

Line planning is an important step to determine the optimal frequencies of trains given the forecasted demand for each train type. The main input data for line planning is the leg traffic demand which can be derived using suitable traffic assignment models. However most assignment models require a line plan, in other words, train frequencies or headways, so that inconsistent results just by the procedural approach to find an optimal line plan after determining leg traffic can be avoided. This paper suggests a unified model that can consider the traffic assignment and line planning, simultaneously. We further provide an elaborated approximation algorithm and, finally, provide experimental results determined for the Korean railway network.

• Journal of Information Processing Systems
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• v.14 no.3
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• pp.621-630
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• 2018

Selection of a suitable task from the extensively available large set of tasks is an intricate job for the developers in crowdsourcing software development (CSD). Besides, it is also a tiring and a time-consuming job for the platform to evaluate thousands of tasks submitted by developers. Previous studies stated that managerial and technical aspects have prime importance in bringing success for software development projects, however, these two aspects can be more effective and conducive if combined with human aspects. The main purpose of this paper is to present a conceptual framework for task assignment model for future research on the basis of personality types, that will provide a basic structure for CSD workers to find suitable tasks and also a platform to assign the task directly. This will also match their personality and task. Because personality is an internal force which whittles the behavior of developers. Consequently, this research presented a Task Assignment Model (TAM) from a developers point of view, moreover, it will also provide an opportunity to the platform to assign a task to CSD workers according to their personality types directly.

• Journal of Korean Society of Transportation
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• v.25 no.6
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• pp.161-170
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• 2007

The purpose of this study is to find the solution that overcomes the existing assumption of symmetric cost functions in multi-class assignment. In the assignment problem, the assumption of a symmetric cost function means that the link cost is determined by each unique mode and is not affected by any other modes. In this study, the authors have applied a diagonalized algorithm and a heuristic model based on column generation to a multi-class assignment model and analyzed the result. Through the study, the authors found that the diagonalized algorithm produces equilibrium solutions by the initial convergence condition. In contrast to the diagonalized algorithm, the column generation algorithm has improved the solution model to overcome the problem of equilibrium solutions in the diagonalized algorithm.