• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.5
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• pp.1554-1566
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• 2014

Cloud Computing allows application providers seamlessly scaling their services and enables users scaling their usage according to their needs. In this paper, using queuing game model, we present service scheduling schemes which are used in software as a service (SaaS). The object is maximizing the Cloud Computing platform's (CCP's) payoff via controlling the service requests whether to join or balk, and controlling the value of CCP's admission fee. Firstly, we treat the CCP as one virtual machine (VM) and analyze the optimal queue length with a fixed admission fee distribution. If the position number of a new service request is bigger than the optimal queue length, it balks. Otherwise, it joins in. Under this scheme, the CCP's payoff can be maximized. Secondly, we extend this achievement to the multiple VMs situation. A big difference between single VM and multiple VMs is that the latter one needs to decide which VM the service requests turn to for service. We use a corresponding algorithm solve it. Simulation results demonstrate the good performance of our schemes.

• 한국정보교육학회:학술대회논문집
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• 2011.01a
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• pp.75-82
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• 2011

Addiction to online games has been causing many problems for elementary school students such as school life, humanity, scholarship and physique. Considering the increase in children being addicted to internet games, there are growing needs for attention and countermeasures toward the children. Nevertheless, it leaves something to be desired. Especially, studies and counterplans for the children who live in the metropolitan are not suited with the circumstances of each regional child. Therefore, it's necessary to work out new research by regional student groups. That is why this study understands fundamental facts about the usage of the internet of elementary school students living in Geoje, Gyeongnam and figures out the effects of online game addiction on the formation of character. Also, it suggests the right direction of internet use to parents and teachers, as rousing the public interest about computer game addiction.

• Journal of the Korean Society for Computer Game
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• v.31 no.4
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• pp.91-99
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• 2018

A growing body of research has focused on the negative effects of Internet gaming. This issue has become an increased public health concern in Korea. However, little is known regarding the positive effect of Internet gaming and its etiology. This study examined the effects of gaming motivations on gaming behaviors based on self-determination theory. Specifically, we investigated the associations of intrinsic and extrinsic gaming motivations with adaptive and maladaptive game uses. A cross-sectional data collected from a sample of 3,000 young adults using 2016 Korean Video Gaming Survey was analyzed. Measurement model analysis and structural equation modeling were conducted as primary analyses. The findings highlight the different effects of intrinsic and extrinsic motivations on gaming behaviors, such as adaptive and maladaptive game uses. Intrinsic motivations, such as experience-seeking and achievement-seeking, were associated with adaptive game use. Meanwhile, extrinsic motivations, such as sensation-seeking and monetary reward-seeking, were associated with maladaptive game use. The findings provide a better understanding of video gaming in light of both adaptive and maladaptive game uses. The implications for practice and policy were discussed.

• Journal of Internet Computing and Services
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• v.6 no.4
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• pp.37-46
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• 2005

Computer are being used in an increasingly wide variety of application areas, and their correct operation is often critical for business success and humasn safety. Developing high quality software products is therefore of prime important. The recent game software become popular, so we are interest in the game software testing. According to the kinds of game software, because it has the different characters, so game software testing is very difficult. According to enviroment change, Recently, online game is popular, so online game trade in the world market. In the company, developers try to develop the reliable game software. But we can experience many fault of game software in spite of the beta testing. Especially, Testing is very difficult on the game software because of various environment and functionality. We tried the survey for game user. In this paper, we study the quality testing metric of game software fault basis on the ISO/IEC 9126. Also, we consist of the check list of game software a point of view user. It apply for the reliability testing metrics of ISO/IEC 9126.

• Journal of Korea Game Society
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• v.7 no.4
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• pp.43-51
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• 2007

The game industry, having been recognized as a highly lucrative business, is growing faster as it has gained its foothold not only in domestic but also in foreign markets. As a result, a variety of internet-based games are being loved or simply overlooked by the users all around the world. This study was aimed to investigate the effect of color on the user using RGB, the output value for the monitor, RGB of the background of the game was computed and compared to that of its characters to find out which colors are favored by the users, If we are based on these results, it is considered more easy in understanding the trends of users.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.320-322
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• 2021

With the development of wireless Internet technology and the expansion of the game market, various forms of games are being developed that are mounted on various platforms, including mobile platforms. In this environment, ensuring the immersion of the game user's perspective will secure the game's competitiveness, so it is necessary to increase the immersion by satisfying each area presented by the Human Computer Interaction (HCI) theory. To this end, this high school implemented downhill games and experimented with kiosks by applying an interface that recognizes the human body's movements as a way to secure freedom and immersion of game users.

• International journal of advanced smart convergence
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• v.7 no.1
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• pp.15-23
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• 2018

Spectrum allocation is a key operation in cognitive radio networks (CRNs), where secondary users (SUs) are usually selfish - to achieve itself utility maximization. In view of this context, much prior lit literature proposed spectrum allocation base on non-cooperative game models. However, the most of them proposed non-cooperative game models based on complete information of CRNs. In practical, primary users (PUs) in a dynamic wireless environment with noise uncertainty, shadowing, and fading is difficult to attain a complete information about them. In this paper, we propose a non-cooperative game joint hidden markov model scheme for spectrum allocation in CRNs. Firstly, we propose a new hidden markov model for SUs to predict the sensing results of competitors. Then, we introduce the proposed hidden markov model into the non-cooperative game. That is, it predicts the sensing results of competitors before the non-cooperative game. The simulation results show that the proposed scheme improves the energy efficiency of networks and utilization of SUs.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.11
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• pp.3565-3583
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• 2022

The task scheduling problem has received a lot of attention in recent years as a crucial area for research in the cloud environment. However, due to the difference in objectives considered by service providers and users, it has become a major challenge to resolve the conflicting interests of service providers and users while both can still take into account their respective objectives. Therefore, the task scheduling problem as a bi-objective game problem is formulated first, and then a task scheduling model based on the bi-objective game (TSBOG) is constructed. In this model, energy consumption and resource utilization, which are of concern to the service provider, and cost and task completion rate, which are of concern to the user, are calculated simultaneously. Furthermore, a many-objective evolutionary algorithm based on a partitioned collaborative selection strategy (MaOEA-PCS) has been developed to solve the TSBOG. The MaOEA-PCS can find a balance between population convergence and diversity by partitioning the objective space and selecting the best converging individuals from each region into the next generation. To balance the players' multiple objectives, a crossover and mutation operator based on dynamic games is proposed and applied to MaPEA-PCS as a player's strategy update mechanism. Finally, through a series of experiments, not only the effectiveness of the model compared to a normal many-objective model is demonstrated, but also the performance of MaOEA-PCS and the validity of DGame.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.11 no.6
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• pp.119-126
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• 2011

As a software component for computer game, the physics engine simulates objects' movement according to the laws of physics. This paper introduces a design and implementation of mobile game on the Android platform, where we used JBox2D physics engine library and Android graphics APIs. We borrowed the key idea of this game from Crayon Physics which is known as a famous PC game. This game starts with no way from user character to destination character. The game user has to make a way to destination character from user character by creating polygon objects between them. The user wins when user character meets destination character. However, the game user has to decide the time to create objects and their shapes well because all objects in this game are governed by the laws of physics. As an important thing of this paper, we introduced into this game new input methods of LCD touch and sensors embedded in mobile devices but not in PCs. Game users can create objects by drawing polygons with LCD touch and move objects or characters according to sensor values from accelerator sensors by tilting the mobile device.

• International Journal of Internet, Broadcasting and Communication
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• v.16 no.3
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• pp.192-198
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• 2024

This paper investigates the application of multi-agent deep reinforcement learning in the fighting game Samurai Shodown using Proximal Policy Optimization (PPO) and Advantage Actor-Critic (A2C) algorithms. Initially, agents are trained separately for 200,000 timesteps using Convolutional Neural Network (CNN) and Multi-Layer Perceptron (MLP) with LSTM networks. PPO demonstrates superior performance early on with stable policy updates, while A2C shows better adaptation and higher rewards over extended training periods, culminating in A2C outperforming PPO after 1,000,000 timesteps. These findings highlight PPO's effectiveness for short-term training and A2C's advantages in long-term learning scenarios, emphasizing the importance of algorithm selection based on training duration and task complexity. The code can be found in this link https://github.com/Lexer04/Samurai-Shodown-with-Reinforcement-Learning-PPO.