• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.9
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• pp.3126-3145
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• 2014

Cloud computing is a computing paradigm in which users can rent computing resources from service providers according to their requirements. A spot instance in cloud computing helps a user to obtain resources at a lower cost. However, a crucial weakness of spot instances is that the resources can be unreliable anytime due to the fluctuation of instance prices, resulting in increasing the failure time of users' job. In this paper, we propose a Genetic Algorithm (GA)-based workflow scheduling scheme that can find the optimal task size of each instance in a spot instance-based cloud computing environment without increasing users' budgets. Our scheme reduces total task execution time even if an out-of-bid situation occurs in an instance. The simulation results, based on a before-and-after GA comparison, reveal that our scheme achieves performance improvements in terms of reducing the task execution time on average by 7.06%. Additionally, the cost in our scheme is similar to that when GA is not applied. Therefore, our scheme can achieve better performance than the existing scheme, by optimizing the task size allocated to each available instance throughout the evolutionary process of GA.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2005.05a
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• pp.1117-1123
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• 2005

This paper deals with a new automated guided vehicle (AGV) control system for distributed control. Proposed AGV control system adapts the multi-agent technology. The system is composed of two types of controller: routing and order. The order controller is in charge of assignment of orders to AGVs. Through the bidding-based negotiation with routing controllers, the order controller assigns a new order to the proper AGV. The order controller announces order information to the routing controllers. Then the routing controllers generate a routing schedule for the order and make a bid according to the routing schedule. If the routing schedule conflicts with other AGV's one, the routing controller makes an alternative through negotiation with other routing controllers. The order controller finally evaluates bids and selects one. Each controller consists of a set of agents: negotiation agent, decision making agent and communication agent. We focus on the agent architecture and negotiation-based AGV scheduling algorithm. Proposed system is validated through an exemplary scenario.

• Journal of Information Technology Services
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• v.13 no.2
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• pp.185-194
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• 2014

Recently, as value for practical use of big data is evaluated, companies and organizations that create benefit and profit are gradually increasing with application of big data. But specifical and theoretical study about possible risk factors as introduction of big data is not being conducted. Accordingly, the study extracts the possible risk factors as introduction of big data based on literature reviews and classifies according to big data processing, data collection, data storage, data analysis, analysis data visualization and application. Also, the risk factors have order of priority according to the degree of risk from the survey of experts. This study will make a chance that can avoid risks by bid data processing and preparation for risks in order of dangerous grades of risk.

• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.337-340
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• 1999

At each iteration, the path is either extended by adding a new node, or contracted by deleting its terminal node. When the destination becomes the terminal node of the path, the algorithm terminate. In the process of finding the shortest path to given destination, the algorithm visits other node, there by obtaining a shortest path from the origin to them. We show here that when the auction algorithm is applied to this equivalent program with some special rules for choosing the initial object prices and the person submitting a bid at each iteration, one obtains the generic form of the $\varepsilon$-relaxation method. Thus, the two methods are mathematically equivalent

• Structural Engineering and Mechanics
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• v.45 no.5
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• pp.693-702
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• 2013

Recently, artificial intelligence tools are most used for structural engineering and mechanics. In order to predict reserve prices and prices of awards, this study proposed a novel regression prediction model by the intelligent Kalman filtering method. An artificial intelligent multiple regression model was established using categorized data and then a prediction model using intelligent Kalman filtering. The rather precise construction bid price model was selected for the purpose of increasing the probability to win bids in the simulation example.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2006.11a
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• pp.268-270
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• 2006

The purpose of this paper was to explore delay avoiding measures and strategies. The paper was based on previous work of authors on finding delay causes. Firstly, the paper has discussed about delay avoidance measures prescribed by the previous work. As the previous study identified five main causes of construction delays, various measures and strategies to overcome those delay problems have been discussed in sequence in the last sections. Major delay prevention strategies are: involving stakeholders in the project decisions, outreach program, realistic time and resource estimation, try to adjust the triple constraints of time, cost and scope, ensure fair and complete disclosure of information at an early stage of the construction project, contractor, itself should inquire about patent design errors prior to submitting its bid, owner should include in its contract with the consultant an indemnity (protection) clause etc.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.3
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• pp.382-388
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• 2005

We apply estimations of the intuitionistic fuzzy sets on the basis of which some amendments nay be undertaken. In particular, this paper describes the process of working out a university classes schedule.

• Proceedings of the KSR Conference
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• 2001.05a
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• pp.24-29
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• 2001

Despite of the introduction some sorts of the contract and the bid method like CM(Construction management) that will be efficient to manage the construction project. Korean agencies limit to control project management to do large public constructions. In the case of Taiwan, THSRC is apply J/V system in the public construction project, they are accomplishing that expend optimal the cost and save the construction time. To success J/V it has two factors, one is risk management and another is sharing information of construction project. Therefore, we will study to introduce J/V system to our construction project.

• Journal of Communications and Networks
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• v.18 no.4
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• pp.658-669
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• 2016

The tremendous increase in mobile data traffic coupled with fierce competition in wireless industry brings about spectrum scarcity and bandwidth fragmentation. This inevitably results in asymmetric-valued long term evolution (LTE) spectrum allocation that stems from different timing for twice improvement in capacity between competing operators, given spectrum allocations today. This motivates us to study the economic effects of asymmetric-valued LTE spectrum allocation. In this paper, we formulate the interactions between operators and users as a hierarchical dynamic game framework, where two spiteful operators simultaneously make spectrum acquisition decisions in the upper-level first-price sealed-bid auction game, and dynamic pricing decisions in the lower-level differential game, taking into account user subscription dynamics. Using backward induction, we derive the equilibrium of the entire game under mild conditions. Through analytical and numerical results, we verify our studies by comparing the latest result of LTE spectrum auction in South Korea, which serves as the benchmark of asymmetric-valued LTE spectrum auction designs.

• International Journal of Contents
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• v.14 no.4
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• pp.57-64
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• 2018

Among many UNESCO world heritage sites in Korea, "Historic Village: Hahoe" is adjacent to Nakdong River and it is imperative to monitor the water level near the village in a bid to forecast floods and prevent disasters resulting from floods.. In this paper, we propose a recurrent neural network with multiple hidden layers to predict the water level near the village. For training purposes on the proposed model, we adopt the sixth-order error function to improve learning for rare events as well as to prevent overspecialization to abundant events. Multiple hidden layers with recurrent and crosstalk links are helpful in acquiring the time dynamics of the relationship between rainfalls and water levels. In addition, we chose hidden nodes with linear rectifier activation functions for training on multiple hidden layers. Through simulations, we verified that the proposed model precisely predicts the water level with high peaks during the rainy season and attains better performance than the conventional multi-layer perceptron.