• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.8A
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• pp.828-834
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• 2010

In this paper, an adaptive cross-layer resource allocation algorithm for the downlink multi-user OFDM system is proposed. The proposed algorithm does not only concern the wireless characteristics of physical (PHY) layer, but also pays attention to the user's quality of service (QoS) requirement, fairness, and packet queue state information of medium access control (MAC) layer. The algorithm is composed of two parts: one is to decide the priority of the user, and the other is to assign the radio resource according to its priority. Simulation results show that the proposed algorithm has both steady QoS and low computation complexity, even though the mobile users have different receiving signal to noise ratio (SNR).

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.15 no.6
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• pp.440-448
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• 2022

Recently, due to the introduction of distributed energy resources, the optimal resource allocation problem of the power network is more and more important, and the distributed resource allocation method is required to process huge amount of data in large-scale power networks. In the optimal resource allocation problem, many studies have been conducted on the case when the supply-demand balance is satisfied due to the limitation of the generation capacity of each generator, but the studies considering the supply-demand imbalance, that total demand exceeds the maximum generation capacity, have rarely been considered. In this paper, we propose the consensus-based distributed algorithm for the optimal resource allocation of power network considering the supply-demand imbalance condition as well as the supply-demand balance condition. The proposed distributed algorithm is designed to allocate the optimal resources when the supply-demand balance condition is satisfied, and to measure the amount of required resources when the supply-demand is imbalanced. Finally, we conduct the simulations to verify the performance of the proposed algorithm.

• Journal of Information Processing Systems
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• v.18 no.3
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• pp.389-401
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• 2022

The business of Internet of Vehicles (IoV) is growing rapidly, and the large amount of data exchange has caused problems of large mobile network communication delay and large energy loss. A strategy for resource allocation of IoV communication based on mobile edge computing (MEC) is thus proposed. First, a model of the cloud-side collaborative cache and resource allocation system for the IoV is designed. Vehicles can offload tasks to MEC servers or neighboring vehicles for communication. Then, the communication model and the calculation model of IoV system are comprehensively analyzed. The optimization objective of minimizing delay and energy consumption is constructed. Finally, the on-board computing task is coded, and the optimization problem is transformed into a knapsack problem. The optimal resource allocation strategy is obtained through genetic algorithm. The simulation results based on the MATLAB platform show that: The proposed strategy offloads tasks to the MEC server or neighboring vehicles, making full use of system resources. In different situations, the energy consumption does not exceed 300 J and 180 J, with an average delay of 210 ms, effectively reducing system overhead and improving response speed.

• Journal of Korean Institute of Industrial Engineers
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• v.23 no.2
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• pp.433-450
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• 1997

In this study, a heuristic algorithm is developed to solve a resource-constrained scheduling problem. The problem involves multiple projects and multiple resource categories, and allows flexible resource allocation to each activity. The objective is to minimize the maximum completion time. The algorithm takes advantage of the basic structure of a heuristic algorithm, called the exchange heuristic, but employs different strategies on some critical steps of the original algorithm which have significant effects on the algorithm performance. The original algorithm and the modified algorithm were compared through an experimental investigation. The modified algorithm produces significantly shorter schedules than the original algorithm, though it requires up to three times more computation time.

• Journal of Digital Convergence
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• v.14 no.10
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• pp.303-310
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• 2016

Due to the ossification of the Internet, it is difficult to accommodate variety services. One of the efficient solution to this problem is network virtualization. It allows multiple parallel virtual networks to run on the shared physical infrastructure. It needs new resource allocation mechanism to share efficient physical resources. In this paper, we present efficient bandwidth allocation algorithm for virtual network request with high service priority. Our proposed algorithm can withdraw allocated bandwidth from low-level priority virtual network and maintain low-level virtual network service. We evaluated the performance of our proposed algorithm using simulation and found the improvement of approximately 8% acceptance rate.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2004.05a
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• pp.167-170
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• 2004

This paper proposes resource allocation method for achieving investment goals in manufacturing system. In order to align resource allocation and manufacturing system design, the system design decomposition (SDD) approach is used. In this paper, a mathematical formulation for resource allocation based on SDD approach is analyzed and a genetic algorithm application is discussed.

• Proceedings of the IEEK Conference
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• 2000.11b
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• pp.329-332
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• 2000

This paper proposed resource allocation algorithm for the minimum power consumption of functional unit in high level synthesis process as like DSP which is circuit to give many functional unit. In this paper, the proposed method though high level simulation find switching activity in circuit each functional unit exchange for binary sequence length and value bit are logic one value. To used the switching activity find the allocation with minimal power consumption, the proposed method visits all control steps one by one and determines the allocation with minimal power consumption at each control step.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.11a
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• pp.417-420
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• 2006

This paper suggests that resource allocation algorithm in multiuser orthogonal frequncy divisioin multiplexing (OFDM). The proposed algorithm considers throughput maximization with power constraint and quality of service (QoS) constraint. This problem has a optimal solution with using well known water-filling algorithm but the algorithm requires high computational complexity. Therefore the problem needs a sub-optimal algorithm for decreasing computational complexity. We propose a sub-optimal joint subcarrier and power allocation algorithm for multiuser OFDM system and compare with previous resource allocation algorithm.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.4
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• pp.1471-1488
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• 2018

Interference mitigation is a significant issue in the cognitive heterogeneous networks, this paper studied how to reduce the interference to macrocell users (MU) and improve system throughput. Establish the interference model with imperfect spectrum sensing by analyzing the source of interference complexity. Based on the user topology, the optimize problem was built to maximize the downlink throughput under given interference constraint and the total power constraint. We decompose the resource allocation problem into subcarrier allocation and power allocation. In the subcarrier assignment step, the allocated number of subcarriers satisfies the requirement of the femtocell users (FU).Then, we designed the power allocation algorithm based on the Lagrange multiplier method and the improved water filling method. Simulation results and performance analyses show that the proposed algorithm causes less interference to MU than the algorithm without considering imperfect spectrum sensing, and the system achieves better throughput performance.

• Journal of Korean Institute of Industrial Engineers
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• v.28 no.1
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• pp.14-24
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• 2002

We focus on resource allocation planning in container terminal operation planning problems and present network design model and genetic algorithm. We present a network design model in which arc capacities must be properly dimensioned to sustain the container traffic. This model supports various planning aspects of container terminal and brings in a very general form. The integer programming model of network design can be extended to accommodate vertical or horizontal yard configuration by adding constraints such as restricting the sum of yard cranes allocated to a block of yards. We devise a genetic algorithm for the network design model in which genes have the form of general integers instead of binary integers. In computational experiments, it is found that the genetic algorithm can produce very good solution compared to the optimal solution obtained by CPLEX in terms of computation time and solution quality. This algorithm can be used to generate many alternatives of a resource allocation plan for the container terminal and to evaluate the alternatives using various tools such as simulation.