• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.5
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• pp.2243-2257
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• 2019

A heterogeneous cellular network (HCN) is useful to increase the spectral and energy efficiency of wireless networks and to reduce the traffic load from the macro cell. The performance of the secondary user equipment (SUE) is affected by interference from the eNodeB (eNB) in a macro cell. To decrease the interference between the macro cell and the small cell, allocating resources properly is essential to an HCN. This study considers the scenario of a software-defined heterogeneous cellular network and performs the resource allocation process. First, we show the system model of HCN and formulate the optimization problem. The optimization problem is a complex process including power and frequency resource allocation, which imposes an extremely high complexity to the HCN. Therefore, a hierarchical resource allocation scheme is proposed, which including subchannel selection and a particle swarm optimization (PSO)-based power allocation algorithm. Simulation results show that the proposed hierarchical scheme is effective in improving the system capacity and energy efficiency.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.11
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• pp.5357-5381
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• 2018

Cloud computing offers a wide range of on-demand resources over the internet. Utility-based resource allocation in cloud data centers significantly increases the number of cloud users. Heavy usage of cloud data center encounters many problems such as sacrificing system performance, increasing operational cost and high-energy consumption. Therefore, the result of the system damages the environment extremely due to heavy carbon (CO2) emission. However, dynamic allocation of energy-efficient resources in cloud data centers overcomes these problems. In this paper, we have proposed Energy and Service Level Agreement (SLA) Aware Resource Allocation Heuristic Algorithms. These algorithms are essential for reducing power consumption and SLA violation without diminishing the performance and Quality-of-Service (QoS) in cloud data centers. Our proposed model is organized as follows: a) SLA violation detection model is used to prevent Virtual Machines (VMs) from overloaded and underloaded host usage; b) for reducing power consumption of VMs, we have introduced Enhanced minPower and maxUtilization (EMPMU) VM migration policy; and c) efficient utilization of cloud resources and VM placement are achieved using SLA-aware Modified Best Fit Decreasing (MBFD) algorithm. We have validated our test results using CloudSim toolkit 3.0.3. Finally, experimental results have shown better resource utilization, reduced energy consumption and SLA violation in heterogeneous dynamic cloud environment.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.9
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• pp.4145-4164
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• 2016

Energy harvesting is an increasingly attractive source of power for cellular networks, and can be a promising solution for green networks. In this paper, we consider a cellular network with power beacons powering multiple mobile terminals with microwave power transfer in energy beamforming. In this network, the power beacons are powered by grid and renewable energy jointly. We adopt a dual-level control architecture, in which controllers collect information for a core controller, and the core controller has a real-time global view of the network. By implementing the water filling optimized power allocation strategy, the core controller optimizes the energy allocation among mobile terminals within the same cluster. In the proposed green energy cooperation paradigm, power beacons dynamically share their renewable energy by locally injecting/drawing renewable energy into/from other power beacons via the core controller. Then, we propose a new water filling optimized green energy cooperation management strategy, which jointly exploits water filling optimized power allocation strategy and green energy cooperation in cellular networks. Finally, we validate our works by simulations and show that the proposed water filling optimized green energy cooperation management strategy can achieve about 10% gains of MT's average rate and about 20% reduction of on-grid energy consumption.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.8
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• pp.1825-1842
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• 2013

Rapid growth of the IT industry has led to significant energy consumption in the last decade. Data centers swallow an enormous amount of electrical energy and have high operating costs and carbon dioxide excretions. In response to this, the dynamic consolidation of virtual machines (VMs) allows for efficient resource management and reduces power consumption through the live migration of VMs in the hosts. Moreover, each client typically has a service level agreement (SLA), this leads to stipulations in dealing with energy-performance trade-offs, as aggressive consolidation may lead to performance degradation beyond the negotiation. In this paper we propose a heuristic based resource allocation of VM selection and a VM allocation approach that aims to minimize the total energy consumption and operating costs while meeting the client-level SLA. Our experiment results demonstrate significant enhancements in cloud providers' profit and energy savings while improving the SLA at a certain level.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.21 no.5
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• pp.311-318
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• 2009

In previous study, a new allocation methodology of common cost on multi-product have been suggested. The aim of this study is to suggest the methodology that allocates an environment pollution cost including carbon emission cost to each cost of multi-product. For this study, a supposed multi-energy system composed of twenty kinds of systems was made. The multi-energy system produces eighteen kinds of outputs that are electricity, steam, hot water, chilled water, ice, warm air, and cooling air from seven kinds of energy source that are LNG, coil, geothermal energy, sun heat, hydrogen, bio-mass, and waste. The new methodology was applied to the multi-energy system in order to allocate the environment pollution cost to each production cost, and twenty seven equations were induced. From this result, it is concluded that this methodology can estimate each unit cost and allocate each cost flow in any product of any energy system.

• Journal of Electrical Engineering and Technology
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• v.9 no.3
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• pp.1132-1136
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• 2014

In the context of increasing electric energy consumption in a data center, energy efficiency improvement is strongly emphasized. In a data center, electric energy is largely consumed by DC power supply system, which is based on a rectifier composed by multiple parallel converters. Therefore, rectifier efficiency must be improved for minimizing loss of DC power supply system. Rectifier efficiency can be modulated by load allocation to converters because converter efficiency depends on input AC power. In this paper, we propose a new control method to maximize rectifier efficiency. The method can control load allocation to converters by introducing active power converter control scheme and start-and-stop of converters. In order to illustrate optimal load allocations in a rectifier, a maximization problem of rectifier efficiency is formulated as a nonlinear optimization one. The problem is solved by Lagrangian relaxation method and the computation results provide the validity of proposed method.

• ETRI Journal
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• v.38 no.4
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• pp.746-756
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• 2016

Owing to the intermittent power generation of renewable energy sources (RESs), future wireless cellular networks are required to reliably aggregate power from retailers. In this paper, we propose a distributed power allocation (DPA) scheme for base stations (BSs) powered by retailers with heterogeneous RESs in order to deal with the unreliable power supply (UPS) problem. The goal of the proposed DPA scheme is to maximize our well-defined utility, which consists of power satisfaction and unit power costs including added costs as a non-subscriber, based on linear and quadratic cost models. To determine the optimal amount of DPA, we apply dual decomposition, which separates the master problem into sub-problems. Optimal power allocation from each retailer can be obtained by iteratively coordinating between the BSs and retailers. Finally, through a mathematical analysis, we show that the proposed DPA can overcome the UPS for BSs powered from heterogeneous RESs.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.4
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• pp.130-137
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• 1993

In this paper, A progressive coding of mean difference pyramid by Hadamard transform of the difference between two successive pyramid levels has been studied. A block adaptive bit allocation method based on ac energy of each sub-block has been proposed, which efficiently reduces the final distortion in the progressive transmission of image parameters. In our scheme, the dc energy equals the sum of the quantization errors of the Hadamard transform coefficients at previous level. Therefore proposed allocation method includes the estimation of dc energy at each pyramid level. Computer simulation results show some improvements in terms of MSE and picture quality over the conventional fixed allocation scheme.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.11
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• pp.4595-4610
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• 2020

In the practical communication environment, the accurate channel state information (CSI) is difficult to obtain, which will cause the mismatch of resource and degrade the system performance. In this paper, to account for the channel uncertainties, a robust power allocation scheme for a downlink Non-orthogonal multiple access (NOMA) heterogeneous network (HetNet) is designed to maximize energy efficiency (EE), which can ensure the quality of service (QoS) of users. We conduct the robust optimization model based on worse-case method, in which the channel gains belong to certain ellipsoid sets. To solve the non-convex non-liner optimization, we transform the optimization problem via Dinkelbach method and sequential convex programming, and the power allocation of small cell users (SCUs) is achieved by Lagrange dual approach. Finally, we analysis the convergence performance of proposed scheme. The simulation results demonstrate that the proposed algorithm can improve total EE of SCUs, and has a fast convergence performance.

• New & Renewable Energy
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• v.16 no.4
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• pp.33-40
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• 2020

The research topics of more than 1,900 wind energy papers registered in the Korean Journal Citation Index (KCI) were modeled into 25 topics using latent directory allocation (LDA), and their consistency was cross-validated through principal component analysis (PCA) of the document word matrix. Key research topics in the wind energy field were identified as "offshore, wind farm," "blade, design," "generator, voltage, control," 'dynamic, load, noise," and "performance test." As a new method to determine the similarity between research topics in journals, a systematic evaluation method was proposed to analyze the correlation between topics by constructing a journal-topic matrix (JTM) and clustering them based on topic similarity between journals. By evaluating 24 journals that published more than 20 wind energy papers, it was confirmed that they were classified into meaningful clusters of mechanical engineering, electrical engineering, marine engineering, and renewable energy. It is expected that the proposed systematic method can be applied to the evaluation of the specificity of subsequent journals.