• 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.

• Journal of Korea Game Society
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• v.2 no.1
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• pp.36-41
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• 2002

Recently, The online role playing games (RPG) get into spotlight of worldwide game marketing area because of the rapid growth of high speed Internet environment during a decade. The almost online RPGs are made of campaign scenario that constructed in series. In this paper, we propose the Distributed Server Model for the Evolutionary Online RPGs which have series scenario (Campaign). In order to represents evolutionary online RPGs, We configure the online RPG server uniquely by means of one to one mapping between logical and physical game world. We also configure the game worlds using circular queue form to express the evolution of civilization by reconstruction of game world.

• International Journal of Computer Science & Network Security
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• v.22 no.9
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• pp.1-6
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• 2022

Teaching and learning are one of the major issues during this pandemic (COVID-19). Since the pandemic started, there are many changes in teaching and learning styles as everything related to studies started online. Game-Based Learning has got remarkable importance in the educational system and pedagogy as an effective way of increasing student inspiration and engagement. In this field, most of the work has been carried out in digital games. This research uses an Animated Game-Based Learning design in enhancing student engagement and perception of learning. In teaching Computer Science (CS) concepts in higher education, to enhance the pedagogy activities in CS concepts, more specifically the concepts of "Data Structures (DS)" i.e., Array, Stack, and Queue concepts are focused. This study aims to observe the difference in students' learning with the use of different learning methods i.e., the traditional learning (TL) method and the Animated Game-Based Learning (AGBL) Method. The experimental results show that learning DS concepts has been improved by the AGBL method as compared to the TL method.

• Management Science and Financial Engineering
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• v.1 no.1
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• pp.1-19
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• 1995

In this paper, we analyze an M / M / 1 queueing system where there are incentive conflicts among customers. Self-interested customers' decisions whether to join the system or not may not necessarily induce a socially optimal congestion level. As a way to alleviate the over-congestion, toll imposition was used in Naor's paper [3]. Instead of using a toll mechanism, we study the usefulness of imperfect information on system state (queue size, for example) as a way to reduce the over-congestion by self-interested customers. The main conclusion of this paper is that by purposefully giving fuzzy or imperfect information on the current queue size we can improve the congestion in the system. This result might look contradictory to rough intuition since perfect information should give better performance than imperfect information. We show how this idea is verified. In deriving this result, we use the concept of Nash equilibrium (pure and mixed strategy) as introduced in game theory. In some real situations, using imperfect information is easier to apply than imposing a toll, and thus the result of this paper has practical implications.

• Journal of Korea Game Society
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• v.15 no.6
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• pp.97-106
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• 2015

In an Unity engine for multi-player online games, the main thread processing game logic must be separated from the network thread that is responsible for network packet communication. Packet communication between the network threads needs to drop packets that overlap in order to improve the rendering speed. In this paper, the packet discard policy of network thread is proposed for an Unity engine for multi-player online games. The proposed method is the hybrid method of both Partial Packet Discard and Periodic Packet Discard methods to improve the rendering speed by periodically discarding overlapped network packets managed by the queue. The rendering speed of the proposed method is analyzed and its effectiveness is verified by various packet generating simulations of the Unity engine for multi-player online games.

• Journal of the Korea Society for Simulation
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• v.17 no.4
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• pp.61-69
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• 2008

In order to evaluate the performance of priority queues for future event list in discrete-event simulations, models representing patterns of enqueue and dequeue processes are required. The time complexities of diverse priority queue implementations can be compared using the performance models. This study aims at developing such performance models especially under the environment that a developed simulation model is used repeatedly for a long period. The developed performance model is based on multi-stage Markov process models; probabilistic patterns of enqueue and dequeue are considered by incorporating non-homogeneous transition probability. All necessary parameters in this performance model would be estimated by analyzing a results obtained by executing the simulation model. A case study with a war game simulation model shows how the parameters defined in muti-stage Markov process models are estimated.