• Journal of the Korean Regional Science Association
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• v.13 no.2
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• pp.75-92
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• 1997

This paper is concerned with an estimation of optimal investment of road sector in 1996-2005. The main method is a Computable General Equilibrium (CGE) Model for Korea in which the optimal solution is derived in a recursively dynamic path. The model is composed of three main modules: the supply, the demand and the price. In this paper, the investment demand for the road is optimized with subject to national economic growth and price inflation. If the annual inflation level and the economic growth rate during 1996-2005 are set to 4.5%-5.0% and 6.0%-6.5% respectively, the optimal demand for the road investment is estimated as 155.1-180.1 trillion Won or 3.33%-3.89% of the GDP for ten years. It implies that the additional increase of the road investment by 0.61%-1.15% of the GDP is required for sustainable economic development, since the share of the road investment in the GDP of the latest 5 years has stayed around 2.27%. However, it is necessary to reduce construction investments on housing as well as to promote private financing of the road in order to maximize an efficiency of resource allocation.

• Journal of information and communication convergence engineering
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• v.17 no.1
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• pp.21-40
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• 2019

This paper presents a comprehensive survey of various artificial intelligence (AI) techniques implemented in cognitive radio engine to improve cognition capability in cognitive radio networks (CRNs). AI enables systems to solve problems by emulating human biological processes such as learning, reasoning, decision making, self-adaptation, self-organization, and self-stability. The use of AI techniques is studied in applications related to the major tasks of cognitive radio including spectrum sensing, spectrum sharing, spectrum mobility, and decision making regarding dynamic spectrum access, resource allocation, parameter adaptation, and optimization problem. The aim is to provide a single source as a survey paper to help researchers better understand the various implementations of AI approaches to different cognitive radio designs, as well as to refer interested readers to the recent AI research works done in CRNs.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.11
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• pp.3876-3895
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• 2014

Recently, Heterogeneous Network (HetNet) with Coordinated Multi-Point (CoMP) scheme is introduced into Long Term Evolution-Advanced (LTE-A) systems to improve digital services for User Equipments (UEs), especially for cell-edge UEs. However, Radio Resource Management (RRM), including Resource Block (RB) scheduling and Power Allocation (PA), in this scenario becomes challenging, due to the intercell cooperation. In this paper, we investigate the RRM problem for downlink transmission of HetNet system with Joint Processing (JP) CoMP (both joint transmission and dynamic cell selection schemes), aiming at maximizing weighted sum data rate under the constraints of both transmission power and backhaul capacity. First, joint RB scheduling and PA problem is formulated as a constrained Mixed Integer Programming (MIP) which is NP-hard. To simplify the formulation problem, we decompose it into two problems of RB scheduling and PA. For RB scheduling, we propose an algorithm with less computational complexity to achieve a suboptimal solution. Then, according to the obtained scheduling results, we present an iterative Karush-Kuhn-Tucker (KKT) method to solve the PA problem. Extensive simulations are conducted to verify the effectiveness and efficiency of the proposed algorithms. Two kinds of JP CoMP schemes are compared with a non-CoMP greedy scheme (max capacity scheme). Simulation results prove that the CoMP schemes with the proposed RRM algorithms dramatically enhance data rate of cell-edge UEs, thereby improving UEs' fairness of data rate. Also, it is shown that the proposed PA algorithms can decrease power consumption of transmission antennas without loss of transmission performance.

• Journal of the Semiconductor & Display Technology
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• v.17 no.1
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• pp.12-20
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• 2018

Recently, web-based service software has been used as to combine various information or to share information according to the needs of users and the convergence of specialized fields and individual dependent systems. According to the necessity of the user, the proper service environment and the selective service environment according to the purpose and the needs of the user have been studied in a variety of specialized and combined professional research fields and industries. Software based on cloud systems and web services is being used as a tool for appropriate group and user groups and roles. A service system combined dynamically needs a module to manage a user through internal logic and grant a service access authentication. Therefore, it has been considered various approaches that a user who accesses the system is given a service access authority for a certain period of time. Also, when the deadline is over, the authority that you are given to access system will go through the process of expire the right. In this paper, we define the roles of users who access web services, manage user rights according to each role, and provide appropriate service resources to users according to their rights and session information. We analyzed the procedure of constructing the algorithm for the service according to the procedure of each user accessing the web service, granting the service resource and constructing a new role.

• ETRI Journal
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• v.40 no.6
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• pp.745-758
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• 2018

A wide range of studies in various disciplines has focused on the Internet of Things (IoT) and cyber-physical systems (CPS). However, it is necessary to summarize the current status and to establish future directions because each study has its own individual goals independent of the completion of all IoT applications. The absence of a comprehensive understanding of IoT and CPS has disrupted an efficient resource allocation. To assess changes in the knowledge structure and emerging technologies, this study explores the dynamic research trends in IoT by analyzing bibliographic data. We retrieved 54,237 keywords in 12,600 IoT studies from the Scopus database, and conducted keyword frequency, co-occurrence, and growth-rate analyses. The analysis results reveal how IoT technologies have been developed and how they are connected to each other. We also show that such technologies have diverged and converged simultaneously, and that the emerging keywords of trust, smart home, cloud, authentication, context-aware, and big data have been extracted. We also unveil that the CPS is directly involved in network, security, management, cloud, big data, system, industry, architecture, and the Internet.

• ETRI Journal
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• v.43 no.5
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• pp.799-811
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• 2021

This paper considers a challenging problem: to simultaneously optimize the cost and the quality of service in opaque wavelength division multiplexing (WDM) networks. An optimization problem is proposed that takes the information including network topology, traffic between end nodes, and the target level of congestion at each link/ node in WDM networks. The outputs of this problem include routing, link channel capacities, and the optimum number of switch ports locally added/dropped at all switch nodes. The total network cost is reduced to maintain a minimum congestion level on all links, which provides an efficient trade-off solution for the network design problem. The optimal information is utilized for dynamic traffic in WDM networks, which is shown to achieve the desired performance with the guaranteed quality of service in different networks. It was found that for an average link blocking probability equal to 0.015, the proposed model achieves a net channel gain in terms of wavelength channels (𝛾_w) equal to 35.72 %, 39.09 %, and 36.93 % compared to shortest path first routing and 𝛾_w equal to 29.41 %, 37.35 %, and 27.47 % compared to alternate routing in three different networks.

• Journal of Advanced Navigation Technology
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• v.20 no.3
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• pp.238-245
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• 2016

There are technological, operational and environmental constraints at tactical edge, which are disconnected operation, intermittent connectivity, and limited bandwidth (DIL), size, weight and power (SWaP) limitations, ad-hoc and mobile network, and so on. To overcome these limitations and constraints, we use service-oriented architecture (SOA) based technologies. Moreover, the operation environment is highly dynamic: requirements change in response to the emerging situation, and the availability of resources needs to be updated constantly due to the factors such as technical failures. In order to use appropriate resources at the right time according to the mission, it needs to find the best resources. In this context, we identify ontology-based mission service model including mission, task, service, and resource, and develop capability-based matching in tactical edge environment. The goal of this paper is to propose a capability-based semantic matching for dynamic resource allocation. The contributions of this paper are i) military domain ontologies ii) semantic matching using ontology relationship; and (iii) the capability-based matching for the mission service model.

• Journal of the Korea Society of Computer and Information
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• v.18 no.7
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• pp.11-21
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• 2013

Recently operating a large scale computing resource like a data center becomes easier because of the virtualization technology that virtualize servers and enable flexible resource provision. The most of public cloud services provides automatic scaling in the form of scale-in or scale-out and these scaling approaches works well to satisfy the service level agreement (SLA) of users. However, a novel scaling approach is required to operate private clouds that has smaller amount of computing resources than vast resources of public clouds. In this paper, we propose a hybrid server scaling architecture and related algorithms using both scale-in and scale-out to achieve higher resource utilization rate for private clouds. We uses dynamic resource allocation and live migration to run our proposed algorithm. Our propose system aims to provide a fine-grain resource scaling by steps. Thus private cloud systems are able to keep stable service and to reduce server management cost by optimizing server utilization. The experiment results show that our proposed approach performs better in resource utilization than the scale-out approach based on the number of users.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.40 no.12
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• pp.83-93
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• 2003

Differentiated service networks, based on bandwidth broker, perform the control and management of QoS provisioning for the QoS guaranteed services, However, the centralized bandwidth broker model has a scalability problem since it has centralized resource management for the admission control function of all call attempts, Therefore, in this paper, we proposea novel adaptive admission control mechanism according to the attempted call status for enhancing the scalability under the centralized bandwidth broker model in IP differentiated service networks, The proposed mechanism decouples the function of admission control from the bandwidth broker, So, the ingress edge node performs the admission control and the bandwidth broker performs the resource management and QoS provisioning, We also introduce an edge-to-edge path concepts and the ingress edge node performs the admission control under the allocated bandwidth to eachpath. The allocated bandwidth per path adaptively varies according to the status of the attempted calls, This mechanism can significantly reduce the number of communication message between the bandwidth broker and each edge node in the network and increase the bandwidth utilization via adaptable resource allocation, In this paper we study the adaptive admission control operation and show the efficient and extensive improvement through the performance evaluation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.5A
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• pp.391-400
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• 2009

Recently, cellular communication networks are migrating from 2G to 3G. Spectrum utilization tends to be inefficient during the transition. Cognitive radio (CR) technology can be a key solution to increase spectrum efficiency by allowing secondary networks to utilize frequency resource of primary networks. However, conventional CR approaches which do not utilize the frequency reuse factor of primary networks may incur degradation of whole network performance. In this paper, we propose a mechanism that a secondary network senses pilot signals of a primary network and select optimum frequency bands. In order to maximize whole network performance, we formulate an optimization problem subject to interference constraints for a primary network and present algorithms. Simulation results compare the proposed method with the conventional method. Our proposed method shows performance gain over the conventional method if channel variation of a primary network is dynamic and the frequency reuse factor of a primary network is high.