• ETRI Journal
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• v.42 no.6
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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.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.11a
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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.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.3A
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• pp.223-232
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• 2004

In this paper we propose the hierarchical-based dynamic bandwidth allocation algorithm for multi-class services in Ethernet-PON. The proposed algorithm consists of the high level scheduler in OLT and the low level scheduler in ONU. The hierarchical architecture is able to provide scalability and resource efficiency in Ethernet-PON which has the distributed nature of the scheduling domain, with queues and the scheduler located at a large distance from each other. We also propose three dynamic bandwidth allocation algorithms for the low level scheduler: Proportional Allocation algorithm, Maximum Request First Allocation (MRFA) algorithm and High Priority First Allocation (HPFA) algorithm. We implement the Ethernet-PON standardized in the IEEE 802,3ah using OPNET. We also evaluate and analyze the performance for the proposed algorithms in terms of channel utilization, queuing delay and the amount of remainder.

• ETRI Journal
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• v.44 no.6
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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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• v.8 no.4
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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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• v.13 no.8
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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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• v.14 no.1
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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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• 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.

• KIPS Transactions on Computer and Communication Systems
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• v.5 no.5
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• pp.103-108
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• 2016

In this paper, we propose a resource allocation scheme that guarantees transmission rate for each mobile stations by mitigating interference between a base station-to-mobile station link and a relay station-to-mobile station link. Specifically, we dynamically adjust the boundary between access zone and relay zone using signal to interference plus noise ratio. Moreover, we cluster the mobile stations under sever interference and manage the channel quality of these mobile stations by allocating additional radio resource. Our simulation results show that the proposed scheme can improve the efficiency of radio resources and ensure fairness among mobile stations.

• Journal of KIBIM
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• v.7 no.3
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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.