• The Transactions of the Korean Institute of Electrical Engineers A
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• v.52 no.6
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• pp.347-353
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• 2003

In models of imperfect competition of deregulated electricity markets, the key task is to find the Nash equilibrium(NE). The approaches for finding the NE have had two major bottlenecks: computation of mixed strategy equilibrium and treatment of multi-player games. This paper proposes a payoff matrix approach that resolves these bottlenecks. The proposed method can efficiently find a mixed strategy equilibrium in a multi-player game. The formulation of the m condition for a three-player game is introduced and a basic computation scheme of solving nonlinear equalities and checking inequalities is proposed. In order to relieve the inevitable burden of searching the subspace of payoffs, several techniques are adopted in this paper. Two example application problems arising from electricity markets and involving a Cournot and a Bertrand model, respectively, are investigated for verifying the proposed method.

• Transactions of the Korean Society of Automotive Engineers
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• v.12 no.4
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• pp.191-197
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• 2004

This paper presents experimental results for human drivers' driving patterns and an Adaptive Cruise Control(ACC) strategy. Analyses have shown that female drivers' driving characteristic values such as time-gap and minimum clearance are larger than those of male drivers'. Human drivers tend to have more clearance margins at high speed than at low speed. At low speed, drivers are much more sensitive to the desired clearance than at high speed. A multi-vehicle detection method is presented to improve ride quality of an ACC. Simulation results have shown that the proposed ACC can provide superior performance compared to the ACC strategy which uses a single-vehicle detection method.

• Journal of Information Technology Applications and Management
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• v.16 no.1
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• pp.1-20
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• 2009

Negotiation is a process of reaching an agreement on the terms of a transaction. such as price, quantity, for two or more parties. Negotiation tries to maximize the benefits for all parties concerned. instead of using human-based negotiation. the e-commerce environment provides such an environment as adopting automated negotiation. Thus. choosing agent technology is appropriate for an automatic electronic negotiation platform. since autonomous software agents strive for the best deal on behalf of the human participants. Negotiation agents need a clear-cut definition of negotiation models or strategies. In reality, most bargaining systems embody nearly one negotiation model. In this article. we present a mobile agent negotiation system with reusable negotiation strategies that allows agents to dynamically embody a user's favorite negotiation strategy which can be preinstalled as a component in the system. We develop a prototype system, which is fully implemented in compliance with FIPA specifications, and then. describe the benefits of using the system.

• The KIPS Transactions:PartB
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• v.10B no.3
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• pp.249-256
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• 2003

The most important problems in the multi-agent system are to accomplish a goal through the efficient coordination of several agents and to prevent collision with other agents. In this paper, we propose a new control strategy for succeeding the goal of the prey pursuit problem efficiently. Our control method uses reinforcement learning to control the multi-agent system and consider the distance as well as the space relationship between the agents in the state space of the prey pursuit problem.

• Journal of Electrical Engineering and Technology
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• v.9 no.2
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• pp.471-477
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• 2014

The novel permanent magnetic actuator (PMA) and its optimal design method were proposed in this paper. The proposed PMA is referred to as the separated permanent magnetic actuator (SPMA) and significantly superior in terms of its cost and performance level over a conventional PMA. The proposed optimal design method uses the evolutionary strategy algorithm (ESA), the kriging meta-model (KMM), and the multi-step optimization. The KMM can compensate the slow convergence of the ESA. The proposed multi-step optimization process, which separates the independent variables, can decrease time and increase the reliability for the optimal design result. Briefly, the optimization time and the poor reliability of the optimum are mitigated by the proposed optimization method.

• Journal of Information Processing Systems
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• v.19 no.4
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• pp.450-464
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• 2023

To address the problems of large system overhead and low timeliness when dealing with task scheduling in mobile edge cloud computing, a task scheduling and resource management strategy for edge cloud computing based on an improved genetic algorithm was proposed. First, a user task scheduling system model based on edge cloud computing was constructed using the Shannon theorem, including calculation, communication, and network models. In addition, a multi-objective optimization model, including delay and energy consumption, was constructed to minimize the sum of two weights. Finally, the selection, crossover, and mutation operations of the genetic algorithm were improved using the best reservation selection algorithm and normal distribution crossover operator. Furthermore, an improved legacy algorithm was selected to deal with the multi-objective problem and acquire the optimal solution, that is, the best computing task scheduling scheme. The experimental analysis of the proposed strategy based on the MATLAB simulation platform shows that its energy loss does not exceed 50 J, and the time delay is 23.2 ms, which are better than those of other comparison strategies.

• Journal of KIISE:Software and Applications
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• v.34 no.5
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• pp.487-501
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• 2007

To achieve high resource utilization for multi-issue DSPs, production compiler commonly includes variants of iterative modulo scheduling algorithm. However, excessive cyclic data dependences, which exist in communication and media processing loops, unduly restrict modulo scheduling freedom. As a result, replicated functional units in multi-issue DSPs are often under-utilized. To address this resource under-utilization problem, our paper describes a novel compiler preprocessing strategy for effective modulo scheduling. The preprocessing strategy proposed capitalizes on two new transformations, which are referred to as cloning and dismantling. Our preprocessing strategy has been validated by an implementation for StarCore SC140 DSP compiler.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.2
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• pp.670-686
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• 2017

MapReduce (MRV1), a popular programming model, proposed by Google, has been well used to process large datasets in Hadoop, an open source cloud platform. Its new version MapReduce 2.0 (MRV2) developed along with the emerging of Yarn has achieved obvious improvement over MRV1. However, MRV2 suffers from long finishing time on certain types of jobs. Speculative Execution (SE) has been presented as an approach to the problem above by backing up those delayed jobs from low-performance machines to higher ones. In this paper, an adaptive SE strategy (ASE) is presented in Hadoop-2.6.0. Experiment results have depicted that the ASE duplicates tasks according to real-time resources usage among work nodes in a cloud. In addition, the performance of MRV2 is largely improved using the ASE strategy on job execution time and resource consumption, whether in a multi-job environment.

• The KIPS Transactions:PartB
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• v.8B no.6
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• pp.601-608
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• 2001

The automated assignment of multiple tasks to executing agents is a key problem in the area of multi-agent systems. In many domains, significant savings can be achieved by reallocating tasks among agents with different costs for handling tasks. The automation of task reallocation among self-interested agents requires that the individual agents use a common negotiation protocol that prescribes how they have to interact in order to come to an agreement on "who does what". In this paper, we introduce the multi-agent Traveling Salesman Problem(TSP) as an example of task reallocation problem, and suggest the Vickery auction as an interagent negotiation protocol for solving this problem. In general, auction-based protocols show several advantageous features: they are easily implementable, they enforce an efficient assignment process, and they guarantce an agreement even in scenarios in which the agents possess only very little domain-specific Knowledge. Furthermore Vickrey auctions have the additional advantage that each interested agent bids only once and that the dominant strategy is to bid one′s true valuation. In order to apply this market-based protocol into task reallocation among self-interested agents, we define the profit of each agent, the goal of negotiation, tasks to be traded out through auctions, the bidding strategy, and the sequence of auctions. Through several experiments with sample multi-agent TSPs, we show that the task allocation can improve monotonically at each step and then finally an optimal task allocation can be found with this protocol.

• The Journal of Information Systems
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• v.23 no.1
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• pp.29-52
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• 2014

As the advance of multi-platform and multi-channel online services, brokerages are now offering three representative online trading systems - HTS(Home Trading Systems), WTS(Web Trading Systems), MTS(Mobile Trading Systems). In this study we investigated and compared the impact of different systems on the performance of brokerages. Using the panel data of 29 brokerages of 4 periods, we empirically tested the impact of online trading systems and the commissions of trading services. We found out that there exist some differences between the impacts of online trading systems based on the platforms. HTS was identified as the main platform for online trading services. However the role of MTS was also significantly identified while WTS showed no significant impact on the brokerage performances. Commission also showed significant negative impact in case of HTS and MTS platforms. Finally, offering MTS was identified as the significant dummy variable influencing the performance of brokerages. The results provides some implication for the multi-platform strategy for online services.