• 전자공학회논문지 IE
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• v.45 no.3
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• pp.50-55
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• 2008

In CDMA system, the number of mobile stations which can be served simultaneously in a base station is limited by the amount of total interference received. Considering the facts, the call admission control method using the effective bandwidth concept is employed in this paper. The bandwidth for a new call and a handoff call is allocated by considering the number of mobile station being served and dynamically assigned by taking account of the blocking rate of new calls and the dropping rate of handoff calls. Also, there is reserved resource for handoff call. We analyze the performance of system according to reserved resource by a simulation study. The more a resource reserved, the less it is the dropping rate of handoff.

• Korean Management Science Review
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• v.10 no.1
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• pp.81-105
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• 1993

The objective of the paper is to develop models for determining the aggregate budget size in long-range R&D planning of KT(Korea Telecom.) and for allocating it by strategically adopted technologies for KT's TOP(Telecommunication-Oriented Paradise) Strategy. In the model of R&D budget size determination, the linear regression analysis is applied. In allocating the R&D expenditure, criteria weighting and technological importance ranking are determined by means of the Analytic Hierarchy Process(AHP) as a decision aid, along with hierarchical representation and pairwse comparisons. R&D budget analysis provides to basic data for the mid-and long-range R&D planning. The model then needs to be adjusted as the TOP project plan becomes specific. Resource allocation model for R&D based on AHP can be used to identify the importance of the technologies for TOP according to short-, mid-, and long-term perspectives without further modification. It is expected that the R&D budget analysis model works as the basis for planning R&D investment strategies and that the resource allocation model for R&D contributes to the effective use of the limited resource.

• ETRI Journal
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• v.36 no.4
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• pp.519-527
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• 2014

An integrated multi-beam satellite and multi-cell terrestrial system is an attractive means for highly efficient communication due to the fact that the two components (satellite and terrestrial) make the most of each other's resources. In this paper, a terrestrial component reuses a satellite's resources under the control of the satellite's network management system. This allows the resource allocation for the satellite and terrestrial components to be coordinated to optimize spectral efficiency and increase overall system capacity. In such a system, the satellite resources reused in the terrestrial component may bring about severe interference, which is one of the main factors affecting system capacity. Under this consideration, the objective of this paper is to achieve an optimized resource allocation in both components in such a way as to minimize any resulting inter-component interference. The objective of the proposed scheme is to mitigate this inter-component interference by optimizing the total transmission power - the result of which can lead to an increase in capacity. The simulation results in this paper illustrate that the proposed scheme affords a more energy-efficient system to be implemented, compared to a conventional power management scheme, by allocating the bandwidth uniformly regardless of the amount of interference or traffic demand.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.6
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• pp.1638-1658
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• 2024

As a crucial development direction for the sixth generation of mobile communication networks (6G), Low Earth Orbit (LEO) satellite networks exhibit characteristics such as low latency, seamless coverage, and high bandwidth. However, the frequent changes in the topology of LEO satellite networks complicate communication between satellites, and satellite power resources are limited. To fully utilize resources on satellites, it is essential to determine the association between satellites before power allocation. To effectively address the satellite association problem in LEO satellite networks, this paper proposes a satellite association-based resource allocation algorithm. The algorithm comprehensively considers the throughput of the satellite network and the fairness associated with satellite correlation. It formulates an objective function with logarithmic utility by taking the logarithm and summing the satellite channel capacities. This aims to maximize the sum of logarithmic utility while promoting the selection of fewer associated satellites for forwarding satellites, thereby enhancing the fairness of satellite association. The problems of satellite association and power allocation are solved under constraints on resources and transmission rates, maximizing the logarithmic utility function. The paper employs an improved Kuhn-Munkres (KM) algorithm to solve the satellite association problem and determine the correlation between satellites. Based on the satellite association results, the paper uses the Lagrangian dual method to solve the power allocation problem. Simulation results demonstrate that the proposed algorithm enhances the fairness of satellite association, optimizes resource utilization, and effectively improves the throughput of LEO satellite networks.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.2
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• pp.484-503
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• 2016

Mobile cloud computing has recently become a new paradigm for the utilization of a variety of shared mobile resources via wireless network environments. However, due to the inherent characteristics of mobile devices, a limited battery life, and a network access requirement, it is necessary for mobile servers to provide a dynamic approach for managing mobile resources efficiently in mobile cloud computing environments. Since on-demand job requests occur frequently and the number of mobile devices is drastically increased in mobile cloud computing environments, a different mobile resource management method is required to maximize the computational power. In this paper, we therefore propose a cooperative, mobile resource sharing method that considers both the inherent properties and the number of mobile devices in mobile cloud environments. The proposed method is composed of four main components: mobile resource monitor, job handler, resource handler, and results consolidator. In contrast with conventional mobile cloud computing, each mobile device under the proposed method can be either a service consumer or a service provider in the cloud. Even though each device is resource-poor when a job is processed independently, the computational power is dramatically increased under the proposed method, as the devices cooperate simultaneously for a job. Therefore, the mobile computing power throughput is dynamically increased, while the computation time for a given job is reduced. We conduct case-based experiments to validate the proposed method, whereby the feasibility of the method for the purpose of cooperative computation is shown.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.2A
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• pp.26-33
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• 2005

Exact prediction of resource demands for future calls enhances the efficiency of the limited resource utilization in resource reservation methods for potential calls in wireless IP networks. In this paper, we propose a LMS-Wiener resource(bandwidth) prediction for future handoff calls, and then an the proposed method is compared with an existing Wiener-based method in terms of prediction error through our simulations. In our simulations, we assume that handoff call arrivals follow a non-Poisson process and each handoff call has an non-exponentially distributed channel holdingtime in the cell, considering that handoff call arrival pattern is not Poisson distribution but non-Poisson for long periods of time in wireless picocellular IP networks. Simulation results show that the prediction error in the proposed method converges to the lower value while in an existing method increase as time is passed. Therefore we may conclude that the proposed method improves the efficiency of resource utilization by more exactly predicting resource demands for future handoff calls than an existing method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.12
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• pp.5701-5722
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• 2018

The continuous increase in the cost of energy production and concerns for environmental sustainability are leading research communities, governments and industries to amass efforts to reduce energy consumption and global $CO_2$ footprint. Players in the information and communication industry are keen on reducing the operational expenditures (OpEx) and maintaining the profitability of cellular networks. Meanwhile, network virtualization has been proposed in this regard as the main enabler for 5G mobile cellular networks. In this paper, we propose a generic framework of slice resource provisioning and customized physical resource allocation for energy-efficiency and quality of service optimization. In resource slicing, we consider user demand and population resources provisioning scheme aiming to satisfy quality of service (QoS). In customized physical resource allocation, we formulate this problem with an integer non-linear programming model, which is solved by a heuristic algorithm based on minimum vertex coverage. The proposed algorithm is compared with the existing approaches, without consideration of slice resource constraints via system-level simulations. From the perspective of infrastructure providers, traffic is scheduled over a limited number of active small-cell base stations (sc-BSs) that significantly reduce the system energy consumption and improve the system's spectral efficiency. From the perspective of virtual network operators and mobile users, the proposed approach can guarantee QoS for mobile users and improve user satisfaction.

• KNOM Review
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• v.22 no.3
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• pp.25-30
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• 2019

For meteorological applications, meaningful results must be derived and provided within time and resource limits. Forecasts through numerous historical data are time-consuming and still have resource limitations in the case of disaster safety-related analyses/predictions such as local typhoon forecasts. Suitable forecasts should be provided without any problems caused by limited physical environmental conditions and when results are to be drawn under time constraints, such as typhoon forecasts and forecast services for flooded areas by road. In this paper, we analyze the application of weather and climate forecasting to provide a suitable forecasting service in both temporal and resource conditions. Through the analysis of execution time according to mesh sizes, it was confirmed that a mesh adjustment can cope with the case of the temporal constraint. In addition, by analyzing the execution time through memory resource control, we confirmed the minimum resource condition that does not affect the performance and the resource usage pattern of the application through the swap and mlock analysis.

• Proceedings of the IEEK Conference
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• 2003.07a
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• pp.57-60
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• 2003

IEEE 802.16 Wireless MAN standard specifies the air interface of fixed point-to-multipoint broadband wireless access systems providing multiple service. Among the service classes supported by the wireless MAN, the BE class is ranked on the lowest position in priority and is usually deployed by multicast and broadcast polling MAC scheme. In provisioning such BE service, the delay performance is influenced by a number of components including restrictions on resource request per SS, the number of request opportunities in upward frame, scheduling requests at BS, and contention resolution method. As candidate components of MAC function for BE service, we propose single and multiple request schemes (for controling the number of requests per SS), exhaustive and limited request schemes (for regulating the amount of grant per request) and FCFS, H-SMF, pure SMF, SS-wise Round Robin, and pure Round Robin (for scheduling requests at BS). Then, we construct MAC schemes by combining the above components and evaluate the delay performance exhibited by each MAC scheme using a simulation method. From numerical results, we investigate the effect of MAC components on average delay and delay variation and observe the dissonance on collision reduction in a resource - limited environment.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.7
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• pp.2496-2512
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• 2021

The requirements for powerful computing capability, high capacity, low latency and low energy consumption of emerging services, pose severe challenges to the fifth-generation (5G) network. As a promising paradigm, mobile edge networks can provide services in proximity to users by deploying computing components and cache at the edge, which can effectively decrease service delay. However, the coexistence of heterogeneous services and the sharing of limited resources lead to the competition between various services for multiple resources. This paper considers two typical heterogeneous services: computing services and content delivery services, in order to properly configure resources, it is crucial to develop an effective offloading and caching strategies. Considering the high energy consumption of 5G base stations, this paper considers the hybrid energy supply model of traditional power grid and green energy. Therefore, it is necessary to design a reasonable association mechanism which can allocate more service load to base stations rich in green energy to improve the utilization of green energy. This paper formed the joint optimization problem of computing offloading, caching and resource allocation for heterogeneous services with the objective of minimizing the on-grid power consumption under the constraints of limited resources and QoS guarantee. Since the joint optimization problem is a mixed integer nonlinear programming problem that is impossible to solve, this paper uses deep reinforcement learning method to learn the optimal strategy through a lot of training. Extensive simulation experiments show that compared with other schemes, the proposed scheme can allocate resources to heterogeneous service according to the green energy distribution which can effectively reduce the traditional energy consumption.