• Proceedings of the Korean Information Science Society Conference
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• 2000.10c
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• pp.576-578
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• 2000

현재의 대부분의 VOD System에서는 Single Server System의 제약인 확장성과 안정적 서비스를 제공하기 위해 Multi-Server System을 사용하고 있다. Multiple Server에 Video Data를 Striping한 구조를 Parallel Video Server Architecture라 한다. 본 연구에서는 Parallel Video Server System 상에서 Data의 Striping Policy에 대해 고찰해보고 이때 발생하는 load balancing과 redundancy 문제의 해결책을 제시하였다. 또한 이를 실제 local Network 시스템에 적용하여 구현하였다.

• Journal of the Korean Operations Research and Management Science Society
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• v.18 no.3
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• pp.51-63
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• 1993

We consider a cyclid server system under N-policy. This system consists of multiple queues served in a cyclic order by a single server. In this paper, we consider the following control policy. Every time server polls one queue, the server inspects the state of the queue. If the total number of units is found to have reached or exceeded a pre-specified value, the server begins to serve the queue until it is empty. As soon as the queue becomes empty, the server polls next queue. An approximate analysis of this system is presented. Sever vacation model is used as an analytical tool. However, server vacation periods are considered to be dependent on the service times of respective queues. The results obtained from the approximate analysis are ompared with simulation results.

• Journal of Korea Game Society
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• v.19 no.3
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• pp.5-14
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• 2019

The gaming server is based on a distributed server. In order to distribute workloads of gaming servers, distributed gaming servers apply some algorithms which divide each of gaming server's workload into balanced workload among the gaming servers and as a result, efficiently manage response time and fusibility of server requested by the clients. In this paper, we propose a load balancing agent using PPO(Proximal Policy Optimization) which is one of the methods from a greedy algorithm and Policy Gradient which is from Reinforcement Learning. The proposed load balancing agent is compared with the previous researches based on the simulation.

• Journal of the Korea Society of Computer and Information
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• v.7 no.4
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• pp.141-149
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• 2002

Recently, a number of network systems are developed rapidly and network architectures are more complex than before, and a policy-based network management should be used in network system. Especially, a new paradigm that policy-based network management can be applied for the network security is raised. A security policy server in the management layer can generate new policy, delete. update the existing policy and decide the policy when security policy is requested. The security server needs to analyze and manage the alert message received from server Policy enforcement system in the enforcement layer for the available information. In this paper, we implement an alert analyzer that analyze the stored alert data for making of security policy efficiently in framework of the policy-based network security management. We also propose a data mining system for the analysis of alert data The implemented mining system supports alert analyzer and the high level analyzer efficiently for the security.

• The Transactions of the Korea Information Processing Society
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• v.6 no.10
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• pp.2790-2796
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• 1999

In video-on-demand systems, the I.O bandwidth of video servers is the critical resource which contributes to increase in latency. Several approaches: bridging, piggybacking are used to reduce the I/O demand on the video server through sharing. Batching delays the requests for the different videos for a batching window so that more requests for the same video arriving during the current batching window may be served using the same stream. In this paper, we propose an adaptive reservation-based batching policy which dynamically reserves video server capacity for popoular videos according to video server loads. The performance of the proposed policy is evaluated through a simulation, and is compared with simple batching and static reservation-based batching policies. As the result, we know that the adaptive reservation-based batching policy more improves service ratio and average waiting time than simple batching and simple reservation-based batching policy more improves service ratio and average waiting time than simple batching and simple reservation-based batching polices.

• The KIPS Transactions:PartC
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• v.9C no.5
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• pp.775-782
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• 2002

This paper introduces Policy Management Tool which was implemented based on Policy Information Model in network suity system. Network security system consists of policy terror managing and sending policies to keep a specific domain from attackers and policy clients detecting and responding intrusion by using policies that policy server sends. Policies exchanged between policy server and policy client are saved in database in the form of directory through LDAP by using Policy Management Tool based on network security policy information model. NSPIM is an extended policy information model of IETF's PCIM and PCIMe, which enables network administrator to describe network security policies. Policy Management Tool based on NSPIM provides not only policy management function but also editing function using reusable object, automatic generation function of object name and blocking policy, and other convenient functions to user.

• Journal of Korea Society of Industrial Information Systems
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• v.21 no.6
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• pp.1-12
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• 2016

In this paper, we consider a general discrete-time queueing system with D-BMAP(discrete-time batch Markovian arrival process) and D-policy. An idle single server becomes busy when the total service times of waiting customer group exceeds the predetermined workload threshold D. Once the server starts busy period, the server provides service until there is no customer in the system. The steady-state workload distribution is derived in the form of generating function. Mean workload is derived as a performance measure. Simulation is also performed for the purpose of verification and a simple numerical example is shown.

• Journal of Korea Society of Industrial Information Systems
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• v.23 no.1
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• pp.53-63
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• 2018

In this paper, we analyze the waiting time of a queueing system with D-BMAP (discrete-time batch Markovian arrival process) and D-policy. Customer group or packets arrives at the system according to discrete-time Markovian arrival process, and an idle single server becomes busy when the total service time of waiting customer group exceeds the predetermined workload threshold D. Once the server starts busy period, the server provides service until there is no customer in the system. The steady-state waiting time distribution is derived in the form of a generating function. Mean waiting time is derived as a performance measure. Simulation is also performed for the purpose of verification and validation. Two simple numerical examples are shown.

• Journal of the Korea Society for Simulation
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• v.13 no.1
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• pp.41-50
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• 2004

The purpose of this paper is to analyse the manager's policy to maximize the profit in a multiple-server queueing facility with a limited queue capacity. We assume that the level of advertizing effects on the arrival rate of customers to the facility. The model without ‘word of mouth effect’ is assumed that the arrival rate is independent on the qualify of service level. We estimate the service quality by the balking rate of customers from system. We extend this to the model with ‘word of mouth effect’. To achieve the maximum profit, the most important factor is the considerably high utilization of facility for both models. Given service rate, we should maintain an effective arrival rate to some extent. To this end, among the available options, an increase of advertizing effort is more desirable than reducing the fee if the service value of customers remains unchanged. We also investigate whether the variability of service time has a significant impact on determining the optimal policy. The cost of service variability is not so expensive as that in a single server model due to the reduced variability of service times in a multiple-server model.

• Journal of the Korean Statistical Society
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• v.31 no.4
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• pp.491-507
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• 2002

We analyze a single server bulk input queue with optional server vacations under a single vacation policy and balking phenomenon. The service times of the customers as well as the vacation times of the server have been assumed to be arbitrary (general). We further assume that not all arriving batches join the system during server's vacation periods. The supplementary variable technique is employed to obtain time-dependent probability generating functions of the queue size as well as the system size in terms of their Laplace transforms. For the steady state, we obtain probability generating functions of the queue size as well as the system size, the expected number of customers and the expected waiting time of the customers in the queue as well as the system, all in explicit and closed forms. Some special cases are discussed and some known results have been derived.