• ETRI Journal
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• 제42권6호
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• pp.846-858
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• 2020

The non-orthogonal multiple access (NOMA) technique offers throughput improvement to meet the demands of the future generation of wireless communication networks. The objective of this work is to further improve the throughput by including an underlay cognitive radio network with an existing multi-carrier NOMA network, using cooperative communication. The throughput is maximized by optimal resource allocation, namely, power allocation, subcarrier assignment, relay selection, user pairing, and subcarrier pairing. Optimal power allocation to the primary and secondary users is accomplished in a way that target rate constraints of the primary users are not affected. The throughput maximization is a combinatorial optimization problem, and the computational complexity increases as the number of users and/or subcarriers in the network increases. To this end, to reduce the computational complexity, a dynamic network resource allocation algorithm is proposed for combinatorial optimization. The simulation results show that the proposed network improves the throughput.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2021년도 추계학술발표대회
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• pp.128-130
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• 2021

Smart cities collect data from thousands of IoT-based sensor devices for intelligent application-based services. Centralized cloud servers support application tasks with higher computation resources but introduce network latency. Fog layer-based data centers bring data processing at the edge, but fewer available computation resources and poor task allocation strategy prevent real-time data analysis. In this paper, tasks generated from devices are distributed as high resource and low resource intensity tasks. The novelty of this research lies in deploying a virtual node assigned to each cluster of IoT sensor machines serving a joint application. The node allocates tasks based on the task intensity to either cloud-computing or fog computing resources. The proposed Task Allocation Strategy provides seamless allocation of jobs based on process requirements.

• 한국통신학회논문지
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• 제29권3A호
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• pp.223-232
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• 2004

본 논문에서는 이더넷 PON(Passive Optical Network)에서 다중 클래스 서비스를 효율적으로 제공하기 위한 동적 대역 할당 알고리듬을 제안한다. 제안한 알고리듬은 OLT(Optical Line Terminal)에 존재하는 상위 단계 스케줄러와 ONU(Optical Network Unit)에 존재하는 하위 단계 스케줄러로 구성된다. 계층적 구조 기반의 대역 할당 알고리듬은 대역 할당을 수행하는 스케줄러와 스케줄의 대상이 되는 큐가 거리 상으로 분산되어 있는 이더넷 PON 시스템에서 확장성과 자원의 효율성을 제공할 수 있다. 또한 본 논문에서는 ONU에서 수행하는 하위 단계 대역 할당 알고리듬으로 비례 할당 알고리듬, 최대 요구 우선 할당(Maximum Request First Allocation: MRFA) 알고리듬, 우선 순위 우선 할당(High Priority First Allocation: HPFA) 알고리듬을 제안한다. 제안한 알고리듬의 성능 평가를 위해 OPNET을 이용하여 IEEE 802.3ah 기반의 이더넷 PON 시스템을 설계하고 시뮬레이션을 수행하였으며 각 알고리듬의 채널 이용률, 큐잉 지연, 잔여대역 관점에서 성능을 평가하고 분석하였다.

• ETRI Journal
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• 제44권6호
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• pp.955-965
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• 2022

A low Earth orbit (LEO) satellite constellation could be used to provide network coverage for the entire globe. This study considers multi-beam frequency reuse in LEO satellite systems. In such a system, the channel is time-varying due to the fast movement of the satellite. This study proposes an efficient power and bandwidth allocation method that employs two linear machine learning algorithms and take channel conditions and traffic demand (TD) as input. With the aid of a simple linear system, the proposed scheme allows for the optimum allocation of resources under dynamic channel and TD conditions. Additionally, efficient projection schemes are added to the proposed method so that the provided capacity is best approximated to TD when TD exceeds the maximum allowable system capacity. The simulation results show that the proposed method outperforms existing methods.

• International Journal of Contents
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• 제8권4호
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• pp.7-11
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• 2012

Cloud Computing can be viewed as a dynamically-scalable pool of resources. Virtualization is one of the key technologies enabling Cloud Computing functionalities. Virtual machines (VMs) scheduling and allocation is essential in Cloud Computing environment. In this paper, two dynamic VMs scheduling and allocating schemes are presented and compared. One dynamically on-demand allocates VMs while the other deploys optimal threshold to control the scheduling and allocating of VMs. The aim is to dynamically allocate the virtual resources among the Cloud Computing applications based on their load changes to improve resource utilization and reduce the user usage cost. The schemes are implemented by using SimPy, and the simulation results show that the proposed adaptive scheme with one threshold can be effectively applied in a Cloud Computing environment both performance-wise and cost-wise.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권8호
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• pp.3821-3841
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• 2019

Cloud radio access networks (C-RANs) have been regarded in recent times as a promising concept in future 5G technologies where all DSP processors are moved into a central base band unit (BBU) pool in the cloud, and distributed remote radio heads (RRHs) compress and forward received radio signals from mobile users to the BBUs through radio links. In such dynamic environment, automatic decision-making approaches, such as artificial intelligence based deep reinforcement learning (DRL), become imperative in designing new solutions. In this paper, we propose a generic framework of autonomous cell activation and customized physical resource allocation schemes for energy consumption and QoS optimization in wireless networks. We formulate the problem as fractional power control with bandwidth adaptation and full power control and bandwidth allocation models and set up a Q-learning model to satisfy the QoS requirements of users and to achieve low energy consumption with the minimum number of active RRHs under varying traffic demand and network densities. Extensive simulations are conducted to show the effectiveness of our proposed solution compared to existing schemes.

• Journal of information and communication convergence engineering
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• 제14권1호
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• pp.21-25
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• 2016

N-screen is a promising technology to improve support for multimedia multicasting, content sharing, content mobility, media scalability, and seamless mobility. In this paper, the WiMedia distributed-MAC (D-MAC) protocol is adopted for development of a seamless N-screen wireless service. Furthermore, to provide a multi-hop, one source multi-use N-screen service through point to point streaming in a seamless D-MAC protocol, a dynamic multi-frame transmission technology is proposed. In this technology, a dynamic time slot allocation scheme and a multi-hop resource reservation scheme are combined. In the proposed dynamic time slot allocation scheme, two thresholds, a hard threshold and a soft threshold, are included to satisfy the power consumption and delay requirements. A multi-frame DRP reservation scheme is proposed to minimize end-to-end delay during the multi-hop transmissions between N-screen devices. The proposed dynamic multi-frame transmission scheme enhances N-screen performance in terms of the multi-hop link establishment success rate and link establishment time compared to the conventional WiMedia D-MAC system.

• ETRI Journal
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• 제36권4호
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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.

• 정보처리학회논문지:컴퓨터 및 통신 시스템
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• 제5권5호
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• pp.103-108
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• 2016

본 논문에서는 멀티 홉 릴레이 네트워크에서 기지국(base station), 중계국(relay station)과 각 단말(mobile station)간의 전송률(throughput)을 향상시킬 수 있는 자원 할당 방법과 간섭을 겪는 단말들의 간섭을 최소화하여 모든 단말의 전송률을 보장하는 방법을 제안하고 있다. 멀티 홉 릴레이 시스템에서 기지국과 릴레이가 주파수 자원을 공유할 수 있으므로 간섭에 취약한 단말들이 생길 수 있다. 본 논문에서는 각 단말의 신호대 잡음 간섭 비(signal to interference plus noise ratio)를 이용하여 엑세스 영역(access zone)과 릴레이 영역(relay zone)의 경계를 동적으로 조절하는 기법과 함께 간섭에 취약한 단말을 분류하고 이를 관리하는 기법을 제안한다. 성능 평가를 통해 제안하는 기법이 무선자원 사용의 효율성을 향상하고 각 단말들의 공평성을 보장하며 네트워크 전체 성능을 향상시키는 것을 확인하였다.

• 한국BIM학회 논문집
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• 제7권3호
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• pp.40-48
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• 2017

It only takes one failed project to wipe out an entire year's profit, when the projects are not managed efficiently. Additionally, escalating costs of materials and a competitive local construction market make subcontractors a challenge. Subcontractors have finite resources that should be allocated simultaneously across many projects in a dynamic manner. Significant scheduling problems are posed by concurrent multi-projects with limited resources. The objective of this thesis is to identify the effect of productivity changes on the total cost resulting from shifting crews across projects using a descriptive model. To effectively achieve the objective, this study has developed a descriptive cost model for a subcontractor with multi-resources and multi-projects. The model was designed for a subcontractor to use as a decision-making tool for resources allocation and scheduling. The model identified several factors affecting productivity. Moreover, when the model was tested using hypothetical data, it produced some effective combinations of resource allocation with associated total costs. Furthermore, a subcontractor minimizes total costs by balancing overtime costs, tardiness penalties, and incentive bonus, while satisfying available processing time constraints.