• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.21 no.4
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• pp.252-259
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• 2009

When various kinds of outputs are produced from a single energy system, the methodology which allocates the common cost to each output cost is very important because it is directly related with the profit and loss of producers and purchasers. In the cost allocation methodology of the heat and the electricity on a cogeneration, there are energy method, work method, proportional method, benefit distribution method, various exergetic methods, and so on. On the other hand, we have proposed a worth evaluation method which can be applied to any system. The definition of this methodology is that the unit cost of a product is proportion to the worth. Where, worth is a certain evaluating basis that can equalize the worth of products. In this study, we applied this methodology to a gas-turbine cogeneration which produces 119.2 GJ/h of electricity and 134.7 GJ/h of steam, and then we allocated 3,150 $/h of fuel cost to electricity cost and steam cost. Also, we compared with various cost allocation methods. As the result, we conclude that reversible work of various kinds of worth basis evaluates the worth of heat and electricity most reasonably.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.9
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• pp.2764-2781
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• 2024

Federated learning (FL) has been proposed as an emerging distributed machine learning framework, which lowers the risk of privacy leakage by training models without uploading original data. Therefore, it has been widely utilized in the Industrial Internet of Things (IIoT). Despite this, FL still faces challenges including the non-independent identically distributed (Non-IID) data and heterogeneity of devices, which may cause difficulties in model convergence. To address these issues, a local surrogate function is initially constructed for each device to ensure a smooth decline in global loss. Subsequently, aiming to minimize the system energy consumption, an FL approach for joint CPU frequency control and bandwidth allocation, called FCBAFL is proposed. Specifically, the maximum delay of a single round is first treated as a uniform delay constraint, and a limited-memory Broyden-Fletcher-Goldfarb-Shanno bounded (L-BFGS-B) algorithm is employed to find the optimal bandwidth allocation with a fixed CPU frequency. Following that, the result is utilized to derive the optimal CPU frequency. Numerical simulation results show that the proposed FCBAFL algorithm exhibits more excellent convergence compared with baseline algorithm, and outperforms other schemes in declining the energy consumption.

• Proceedings of the Korea Society for Energy Engineering kosee Conference
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• 2004.05a
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• pp.213-218
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• 2004

• Journal of KIISE:Computer Systems and Theory
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• v.33 no.9
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• pp.699-708
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• 2006

Bus splitting technique reduces bus energy by placing modules with frequent communications closely and using necessary bus segments in communications. But, previous bus splitting techniques can not be used in MPSoC platform, because it uses cache coherency protocol and all processors should be able to see the bus transactions. In this paper, we propose a bus splitting technique for MPSoC platform to reduce bus energy. The proposed technique divides a bus into several bus segments, some for private memory and others for shared memory. So, it minimizes the bus energy consumed in private memory accesses without producing cache coherency problem. We also propose a task allocation technique considering cache coherency protocol. It allocates tasks into processors according to the numbers of bus transactions and cache coherence protocol, and reduces the bus energy consumption during shared memory references. The experimental results from simulations say the bus splitting technique reduces maximal 83% of the bus energy consumption by private memory accesses. Also they show the task allocation technique reduces maximal 30% of bus energy consumed in shared memory references. We can expect the bus splitting technique and the task allocation technique can be used in multiprocessor platforms to reduce bus energy without interference with cache coherency protocol.

• Journal of the Korea Society of Computer and Information
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• v.29 no.9
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• pp.169-177
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• 2024

Industrial Wireless Sensor Network (IWSN) is a key feature of Industrial IoT that enables industrial automation through process monitoring and control by connecting industrial equipment such as sensors, robots, and machines wirelessly, and must support the strict requirements of modern industrial environments such as real-time, reliability, and energy efficiency. To achieve these goals, IWSN uses reliable communication methods such as multipath routing, fixed redundant resource allocation, and non-contention-based scheduling. However, the issue of wasting redundant resources that are not utilized for communication degrades not only the efficiency of limited radio resources but also the energy efficiency. In this paper, we propose a scheme that utilizes reinforcement learning in communication scheduling to periodically identify unused wireless resources and reallocate them to save energy consumption of the entire industrial network. The experimental performance evaluation shows that the proposed approach achieves about 30% improvement of resource efficiency in scheduling compared to the existing method while supporting high reliability. In addition, the energy efficiency and latency are improbed by more than 21% and 38%, respectively, by reducing unnecessary communication.

• Proceedings of the SAREK Conference
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• 2009.06a
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• pp.1197-1202
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• 2009

Cost allocation on cogeneration is a methodology dividing the input of common cost to electricity cost and heat cost. In the cost allocation methodology of the electricity and heat on a cogeneration, there are energy method, work method, proportional method, benefit distribution method, reversible work method, various exergetic methods, and so on. In previous study, various cost allocation methodologies have been applied and analyzed on a gas-turbine cogeneration producing the 33.1 MW of electricity and the 32.2 Gcal/h of heat, a steam-turbine cogeneration producing the 22.2 MW of electricity and the 44.3 Gcal/h of heat, and combined-cycle cogeneration producing the 314.1 MW of electricity and the 279.4 Gcal/h of heat. In this study, we integrately analyze the results of previous studies and examine the generality and rationality each methodology. Additionally, a new point of view on the values of alternative electricity efficiency and alternative heat efficiency in the previous methodologies was proposed. As the integrated result, we conclude that reversible work method of various common cost allocation methodologies is most rational.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.5
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• pp.871-881
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• 2010

In the uniform price electricity market or bilateral electricity market, the energy transactions in which the network is not considered and ISO's system operation costs which ISO try to minimize are settled separately. In this paper, transmission loss, one of the ISO's system operation costs, was dealt. The conventional marginal loss allocation method gives economic signals but three aspects have to be considered; excessiveness, arbitrariness and cross-subsidy. In this paper, marginal loss compensation efficiency method was suggested which consider those aspects of the conventional marginal loss allocation method. Also the characteristics of the marginal loss compensation efficiency were analyzed in the appendixes. And simple 2-bus system and IEEE 14 bus system were used to explain these characteristics.

• Annual Conference of KIPS
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• 2022.05a
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• pp.45-47
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• 2022

Mobile edge computing (MEC), which enables mobile terminals to offload computational tasks to a server located at the user's edge, is considered an effective way to reduce the heavy computational burden and achieve efficient computational offloading. In this paper, we study a multi-user MEC system in which multiple user devices (UEs) can offload computation to the MEC server via a wireless channel. To solve the resource allocation and task offloading problem, we take the total cost of latency and energy consumption of all UEs as our optimization objective. To minimize the total cost of the considered MEC system, we propose an DRL-based method to solve the resource allocation problem in wireless MEC. Specifically, we propose a Asynchronous Advantage Actor-Critic (A3C)-based scheme. Asynchronous Advantage Actor-Critic (A3C) is applied to this framework and compared with DQN, and Double Q-Learning simulation results show that this scheme significantly reduces the total cost compared to other resource allocation schemes

• IEIE Transactions on Smart Processing and Computing
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• v.6 no.3
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• pp.158-167
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• 2017

Internet-based social and interactive video applications have become major constituents of the envisaged applications for next-generation multimedia networks. However, inherently dynamic network conditions, together with varying user expectations, pose many challenges for resource allocation mechanisms for such applications. Yet, in addition to addressing these challenges, service providers must also consider how to mitigate their operational costs (e.g., energy costs, equipment costs) while satisfying the end-user quality of service (QoS) expectations. This paper proposes a heuristic solution to the problem, where the energy incurred by the applications, and the monetary costs associated with the service infrastructure, are minimized while simultaneously maximizing the average end-user QoS. We evaluate the performance of the proposed solution in terms of serving probability, i.e., the likelihood of being able to allocate resources to groups of users, the computation time of the resource allocation process, and the adaptability and sensitivity to dynamic network conditions. The proposed method demonstrates improvements in serving probability of up to 27%, in comparison with greedy resource allocation schemes, and a several-orders-of-magnitude reduction in computation time, compared to the linear programming approach, which significantly reduces the service-interrupted user percentage when operating under variable network conditions.

• Journal of the Korean Solar Energy Society
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• v.34 no.3
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• pp.21-29
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• 2014

Heliostat field control algorithm is the logics to operate the heliostat field of tower type solar thermal power plant and it could include various methodologies of how to control the heliostat field so as to optimize the energy collection efficiency as well as to reduce the system operating cost. This work, as the first part of the consecutive works, presents heliostat aiming mint allocation scheme which will be used in the heliostat field control algorithm for 200kW solar thermal power plant built in Daegu, Korea. We first discuss the structure of heliostat field control system required for the implementation of aiming scheme developed in this work. Then the methodologies to allocate the heliostat aiming points on the receiver are discussed. The simulated results show that the heliostat aiming point allocation scheme proposed in this work reduces the magnitude of peak heat flux on the receiver more than 40% from the case of which all the heliostats in the field aim at the center of receiver simultaneously. Also it shows that, when the proposed scheme is used, the degradation of heliostat field optical efficiency is relatively small from the maximal optical efficiency the heliostat field could have.