• Journal of Communications and Networks
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• v.10 no.1
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• pp.79-88
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• 2008

In this paper, we propose efficient peer assignment algorithms for low-latency transmission of scalable coded images in peer-to-peer networks, in which peers may dynamically join and leave the networks. The objective of our algorithm is to minimize the transmission time of a requested image that is scalable coded. When an image is scalable coded in different bit rates, the bit stream encoded in a lower bit rate is a prefix subset of the one encoded in a higher bit rate. Therefore, a peer with the same requested image coded in any bit rate, even when it is different from the requested rate, may work as a supplying peer. As a result, when a scalable coded image is requested, more supplying peers can be found in peer-to-peer networks to help with the transfer. However, the set of supplying peers is not static during transmission, as the peers in this set may leave the network or finish their transmission at different times. The proposed peer assignment algorithms have taken into account the above constraints. In this paper, we first prove the existence of an optimal peer assignment solution for a simple identity permutation function, and then formulate peer assignment with this identity permutation as a mixed-integer programming problem. Next, we discuss how to address the problem of dynamic peer departures during image transmission. Finally, we carry out experiments to evaluate the performance of proposed peer assignment algorithms.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.6
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• pp.487-493
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• 2013

As the spread of smart devices that service variety of content, limited mobile terminal channel assignment problem has intensified. In the channel assignment in mobile networks mobile switching center at the request belongs to each base station allocates the channel to the mobile station. This effectively allocate the limited channels of various methods have been proposed for, in this case a hybrid channel allocation using genetic algorithms UHGA (Universal Hybrid Channel Assignment using Genetic Algorithm) in rural areas or urban areas, such as universal network applied to a variety of environments that the efficiency is verified through simulation.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.11a
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• pp.230-235
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• 1996

Eigenstructure (eigenvalues/eigenvectors) assignment has been shown to be a useful tool for flight control system design. In the sense of the eigenstructure assignment, the effectiveness and disturbance suppressibility of a controller depend mainly on the left eigenstructure (eigenvalues/left eigenvectors) of a system. On the other hand, the disturbance decouplability is governed by the right eigenstructure (eigenvalues/right eigenvectors) of the system. In this paper, in order to obtain a disturbance decouplable as well as effective and disturbance suppressible controller, a concurrent assignment methodology of the left and right eigenstructures is proposed. The biorthogonality condition between the left and right modal matrices of a system as well as the relations between the achievable right modal matrix and state selection matrices are used to develop the methodology. The proposed concurrent eigenstructure assignment methodology guarantees that the desired eigenvalues are achieved exactly and the desired left and right eigenvectors are assigned to the best possible(achievable) sets of eigenvectors in the least square sense, respectively. The proposed design methodology is applied to designing a lateral flight control system for an L-1011 aircraft with disturbances.

• Journal of Korean Society of Transportation
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• v.20 no.6
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• pp.99-113
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• 2002

The multi-class traffic assignment problem is the most typical one of the multi-solution traffic assignment problems and, recently formulation of the models and the solution algorithm have been received a great deal of attention. The useful solution algorithm, however, has not been proposed while formulation of the multi-class traffic assignment could be performed by adopting the variational inequality problem or the fixed point problem. In this research, we developed a hybrid solution algorithm which combines GA algorithm, diagonal algorithm and clustering algorithm for the multi-class traffic assignment formulated as a variational inequality Problem. GA algorithm and clustering algorithm are introduced for the wide area and small cost. We also performed an experiment with toy network(2 link) and tested the characteristics of the suggested algorithm.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.4
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• pp.1535-1554
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• 2016

This paper proposes a novel channel assignment scheme called multi-cluster based dynamic channel assignment (MC-DCA) to improve system performance for the downlink of dense femtocell networks (DFNs) based on orthogonal frequency division multiple access (OFDMA) and frequency division duplexing (FDD). In order to dynamically assign channels for femtocell access points (FAPs), the MC-DCA scheme uses a heuristic method that consists of two steps: one is a multiple cluster assignment step to group FAPs using graph coloring algorithm with some extensions, while the other is a dynamic subchannel assignment step to allocate subchannels for maximizing the system capacity. Through simulations, we first find optimum parameters of the multiple FAP clustering to maximize the system capacity and then evaluate system performance in terms of the mean FAP capacity, unsatisfied femtocell user equipment (FUE) probability, and mean FAP power consumption for data transmission based on a given FUE traffic load. As a result, the MC-DCA scheme outperforms other schemes in two different DFN environments for commercial and office buildings.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.11A
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• pp.1035-1046
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• 2005

This paper analyzes the channel assignment techniques and their performance in the On Board Processing (OBP) satellite communication system. It suggests the new Continuous Rate Assignment (CRA) and Dynamic Rare Assignment (DRA) for improving the efficiency of channel assignment at the OBP switch. Mathematical analysis and simulation are given to evaluate the system performance. Aggregate real-time and non-real-time services are considered as different classes. Higher priority is given to voice and video real-time services to avoid delay variation. Onboard scheduler uses CRA and DRA ways to arrange the capacity allocation dynamically. An improved algorithm is given to make the channel more efficient by doing some evaluation of the switching matrix.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.5
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• pp.163-171
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• 2013

This paper proposes an algorithm that seeks the optimal solution for an assignment problem through a simplified process. Generally it is Hungarian algorithm that is prevalently used to solve a given assignment problem. The proposed algorithm reduces 4 steps Hungarian algorithm into 2 steps. Firstly, the algorithm selects the minimum cost from a matrix and deletes the rest of the rows and columns. Secondly, it improves on the solution through reassignment process. For 27 balanced assignment problems and 7 unbalanced problems, the proposed algorithm has successfully yielded the optimal solution, which Genetic algorithm has failed. This algorithm is thus found to be an appropriate replacement of Hungarian algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.3C
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• pp.315-326
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• 2003

Abstract In this paper, an improved index assignment procedure is proposed to reduce the channel error effect in a communication system employing classified vector quantization(CVQ). The proposed algorithm consists of two parts: inner index assignment (IIA) and cross index assignment (CIA). The II A reduces the distortion resulting from the error in order bits, presenting the identity of each code vector in a subcodebook. The CIA modifies the indexes assigned by the IIA in such a way that the effect of the channel error occurring in class bits, indicating the class information of the code vector, can be minimized. Simulation results show that the proposed algorithms enable a reliable communication over noisy channels even without employing the channel encoding. Index Terms Classified vector quantization, index assignment.

• Journal of the military operations research society of Korea
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• v.25 no.1
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• pp.142-159
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• 1999

To assign the soldiers in the adequate positions I military is almost as important as managing officers because they compose the main part of military structure and equipment operators. The current Military Occupational Specialty(MOS) assignment system lacks the capability to optimize the use of recruit's potential. We suggest an MOS assignment method for enlisted recruits using the Analytic Hierarchy Process(AHP) method, this method systematically provides a method of calculation of composite relative weights of decision elements to be considered during MOS assignment and a method of quantification for personal quality of new recruits. The quantified value of personal quality, Mission Performance Capability(MPC), in this study means the mission performance capability when a personnel is assigned to a certain MOS. This paper develops a multiple objectives MOS assignment model for enlisted recruits. It uses MPC of personnels, calculated with AHP method and consensus method, as parameters. The goal constraints are assurance of filling requirement, minimization of the number of unassigned personnel to MOS, capability satisfaction of education facility and support facility, assurance of desired MPC value level for MOS assignment, and maximization of total MPC. The objective function is to terminalization of the negative or positive deviation for the above goal constraints.

• Journal of Korean Institute of Industrial Engineers
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• v.39 no.4
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• pp.253-259
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• 2013

Investment scenarios in the transportation network design problem usually contain installation or expansion of multi-mode transportation links. When one applies the mode choice analysis and traffic assignment sequentially for each investment scenario, it is possible that the travel impedance used in the mode choice analysis is different from the user equilibrium cost of the traffic assignment step. Therefore, to estimate the travel impedance and mode choice accurately, one needs to develop a combined model for the mode choice and traffic assignment. In this paper, we derive the inverse demand and the excess demand functions for the multi-mode multinomial logit mode choice function and develop a combined model for the multi-mode variable demand traffic assignment problem. Using data from the regional O/D and network data provided by the KTDB, we compared the performance of the partial linearization algorithm with the Frank-Wolfe algorithm applied to the excess demand model and with the sequential heuristic procedures.