• Journal of Information Technology Applications and Management
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• v.15 no.1
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• pp.261-270
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• 2008

Wireless Mesh Networks (WMNs) have emerged as one of the new hot topics in wireless communications. WMNs have been suggested for use in situations in which some or all of the users are mobile or are located in inaccessible environments. Unconstrained transmission in a WMN may lead to the time overlap of two or more packet receptions, called collisions or interferences, resulting in damaged useless packets at the destination. There are two types of collisions; primary collision, due to the transmission of the stations which can hear each other, and hidden terminal collision, when stations outside the hearing range of each other transmit to the same receiving stations. For a WMN, direct collisions can be minimized by short propagation and carrier sense times. Thus, in this paper we only consider hidden terminal collision while neglecting direct collisions. To reduce or eliminate hidden terminal collision, code division multiple access (CDMA) protocols have been introduced. The collision-free property is guaranteed by the use of spread spectrum communication techniques and the proper assignment of orthogonal codes. Such codes share the fixed channel capacity allocated to the network in the design stage. Thus, it is very important to minimize the number of codes while achieving a proper transmission quality level in CDMA WMNs. In this paper, an efficient heuristic code assignment algorithm for eliminating hidden terminal collision in CDMA WMNs with general topology.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.4 no.2
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• pp.397-406
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• 2000

Genetic algorithm is used as a means of search, optimization md machine learning, its structure is simple but it is applied to various areas. And it is about an active and effective controller which can flexibly prepare for changeable circumstances. For this study, research about an action base system evolving by itself is also being considered. There is to have a problem that depended entirely on heuristic knowledge of expert forming membership function and control rule for fuzzy controller design. In this paper, for forming the fuzzy control to perform self-organization, we tuned the membership function to the most optimal using a genetic algorithm(GA) and improved the control efficiency by the self-correction and generation of control rules.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.4B
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• pp.455-463
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• 2004

In this paper, we deal with a ring-mesh network design problem arising from the deployment of WDM for the optical internet. The ring-mesh network consists of ring topology and full mesh topology for satisfying traffic demand while minimizing the cost of OAOMs and OXCs. The problem seeks to find an optimal clustering of traffic demands in the network such that the total number of node assignments is minimized, while satisfying ring capacity and node cardinality constraints. We formulate the problem as a mixed-integer programming model and prescribe a tabu search heuristic procedure Promising computational results within 3% optimality gap are obtained using the proposed method.

• ETRI Journal
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• v.39 no.1
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• pp.30-40
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• 2017

In this study, we investigate topology control as a means of obtaining the best possible compromise between the conflicting requirements of reducing energy consumption and improving network connectivity. A topology design algorithm capable of producing network topologies that minimize energy consumption under a minimum-connectivity constraint is presented. To this end, we define a new topology metric, called connectivity efficiency, which is a function of both algebraic connectivity and the transmit power level. Based on this metric, links that require a high transmit power but only contribute to a small fraction of the network connectivity are chosen to be removed. A connectivity-efficiency-based topology control (CETC) algorithm then assigns a transmit power level to each node. The network topology derived by the proposed CETC heuristic algorithm is shown to attain a better tradeoff between energy consumption and network connectivity than existing algorithms. Simulation results demonstrate the efficiency of the CECT algorithm.

• 한국지구물리탐사학회:학술대회논문집
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• 2003.11a
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• pp.176-183
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• 2003

This paper presents a neural network based approach to disseminating information relating to experimental and field observations in engineering. Although the methodology is generic and can be applied to many areas of engineering science, attention is focussed here solely on geotechnical engineering applications. Field data relating to the settlement of foundations presented by Burland and Burbidge (1985) which led to their well known equation for calculation of settlement, now included in most text books, is re-visited. A part of the data, chosen randomly, is used to train an Artificial Neural Network (ANN), which relates foundation settlement to various causes as identified by the authors. Predictions are made for situations for which data were not used in training. These indicate sufficient accuracy when compared to the original field data. Accuracy of predictions is further improved when all the data are included in the training set. The finally trained ANN is shown to represent these data more accurately than the Burland and Burbidge equation. Based on the above heuristic example, an ANN is presented as an alternative to developing equations and design rules in geotechnical engineering practice. Significant advantages are shown to arise by using this methodology. Ease of updating the ANN, as and when additional data becomes available, being the most important one. Loss of transparency, however, seems to be the main disadvantage.

• Journal of Korean Institute of Industrial Engineers
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• v.37 no.4
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• pp.331-341
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• 2011

This paper considers an inbound lot-sizing and outbound dispatching problem for a single product in a thirdparty logistics (3PL) distribution center. Demands are dynamic and finite over the discrete time horizon, and moreover, each demand has a delivery time window which is the time interval with the dates between the earliest and the latest delivery dates All the product amounts must be delivered to the customer in the time window. Ordered products are shipped by multiple vehicle types and the freight cost is proportional to the vehicle-types and the number of vehicles used. First, we formulate a mixed integer programming model. Since it is difficult to solve the model as the size of real problem being very large, we design a conventional genetic algorithm with a local search heuristic (HGA) and an improved genetic algorithm called adaptive genetic algorithm (AGA). AGA spontaneously adjusts crossover and mutation rate depending upon the status of current population. Finally, we conduct some computational experiments to evaluate the performance of AGA with HGA.

• Journal of Information Processing Systems
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• v.16 no.2
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• pp.460-477
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• 2020

As one of the most significant challenges in the virtual data center, the virtual data center embedding has attracted extensive attention from researchers. The existing research works mainly focus on how to design algorithms to increase operating revenue. However, they ignore the energy consumption issue of the physical data center in virtual data center embedding. In this paper, we focus on studying the energy-aware virtual data center embedding problem. Specifically, we first propose an energy consumption model. It includes the energy consumption models of the virtual machine node and the virtual switch node, aiming to quantitatively measure the energy consumption in virtual data center embedding. Based on such a model, we propose two algorithms regarding virtual data center embedding: one is heuristic, and the other is based on particle swarm optimization. The second algorithm provides a better solution to virtual data center embedding by leveraging the evolution process of particle swarm optimization. Finally, experiment results show that our proposed algorithms can effectively save energy while guaranteeing the embedding success rate.

• Journal of Korean Association for Spatial Structures
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• v.15 no.2
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• pp.87-94
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• 2015

This paper aimed at modeling a fine triangular grid for network dome by using Harmony Search (HS) algorithm. For this purpose, an optimization process to find a fine regular triangular mesh on the curved surface was proposed and the analysis program was developed. An objective function was consist of areas and edge's length of each triangular and its standard deviations, and design variables were subject to the upper and lower boundary which was calculated on the nodal connectivity. Triangular network dome model, which was initially consist of randomly irregular triangular mesh, was selected for the target example and the numerical result was analyzed in accordance with the HS parameters. From the analysis results of adopted model, the fitness function has been converged and the optimized triangular grid could be obtained from the initially distorted network dome example.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.9A
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• pp.1101-1107
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• 2004

This paper presents an optimization algorithm and technique for designing parallel Cyclic Redundancy Check (CRC) circuit, which is most widely adopted for error detection A new heuristic algorithm is developed to find as many shared terms as possible, thus eventually to minimize the number and level of the exclusive-or logic blocks in parallel CRC circuits. 16-bit and 32-bit CRC generators are designed with different types of Programmable Logic Devices, and it has been found that our new algorithm and architecture significantly reduce the delay.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.12
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• pp.5212-5230
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• 2016

How to determine the right number of small base stations to activate in multi-cell uplinks to match traffic from a fixed quantity of K users is an open question. This paper analyses the uplink cooperative that jointly receives base stations activation to explore this question. This paper is different from existing works only consider transmitting power as optimization objective function. The global objective function is formulated as a summation of two terms: transmitting power for data and coordinated overhead for control. Then, the joint base stations activation and beamforming problem is formulated as a mixed integer second order cone optimization. To solve this problem, we develop two polynomial-time distributed methods. Method one is a two-stage solution which activates no more than K small base stations (SBSs). Method two is a heuristic algorithm by dual decomposition to MI-SOCP that activates more SBSs to obtain multiple-antennae diversity gains. Thanks to the parallel computation for each node, our methods are more computationally efficient. The strengths and weaknesses of these two proposed two algorithms are also compared using numerical results.