• Journal of Korea Society of Industrial Information Systems
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• v.29 no.2
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• pp.69-80
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• 2024

In this paper, we studied a discrete-time queuing system that operates under a mixed situation of D-policy and T-policy, one of the representative server control policies in queuing theory. A single server serves customers arriving by Bernoulli arrival process on a first-in, first-out basis(FIFO). If there are no customers to serve in the system, the server goes on vacation and returns, until the total service time (i.e., total amount of workload) of waiting customers exceeds predetermined workload threshold D. The operation of the system covered in this study can be used to model the efficient resource utilization of mobile devices using secondary batteries. In addition, it is significant in that the steady state waiting time and system sojourn time of the queuing system under a flexible mixed control policy were derived within a unified framework.

• Journal of Construction Engineering and Project Management
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• v.4 no.2
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• pp.31-40
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• 2014

The management of vehicular supply of "perishable" construction material, such as concrete mixes, faces a series of uncertainties such as weather, daily traffic patterns and accidents. Presented in this paper is a logistics control model for managing a hauling fleet with interrelated processes at both ends and queue capacities. Discrete event simulation is used to model the complex interactions of production units and the randomness of the real world. Two alternative strategies for ready mix concrete delivery, with and without an off-site waiting queue, are studied to compare supply performance. Secondly, the paper discusses the effect of an agent-based GPS tracking system providing real-time travel data that lessens the uncertainty of trucking time. The results show that the combination of GPS information with off-site queuing reduces productivity loss and process wastes of concrete placement as well as the idleness of supply trucks when crew or pump experience an unexpected stoppage.

• Journal of Communications and Networks
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• v.14 no.5
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• pp.578-587
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• 2012

One of the key elements in the emerging, packet-based long term evolution (LTE) cellular systems is the deployment of multiple femtocells for the improvement of coverage and data rate. However, arbitrary overlaps in the coverage of these femtocells make the handover operation more complex and challenging. As the existing handover strategy of LTE systems considers only carrier to interference plus noise ratio (CINR), it often suffers from resource constraints in the target femtocell, thereby leading to handover failure. In this paper, we propose a new efficient, multi-objective handover solution for LTE cellular systems. The proposed solution considers multiple parameters like signal strength and available bandwidth in the selection of the optimal target cell. This results in a significant increase in the handover success rate, thereby reducing the blocking of handover and new sessions. The overall handover process is modeled and analyzed by a three-dimensional Markov chain. The analytical results for the major performance metrics closely resemble the simulation results. The simulation results show that the proposed multi-objective handover offers considerable improvement in the session blocking rates, session queuing delay, handover latency, and goodput during handover.

• Journal of Digital Contents Society
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• v.10 no.2
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• pp.357-365
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• 2009

To effectively exploit the underlying network bandwidth while maximizing user perceivable QoS, mandatory to make proper estimation on packet loss and queuing delay of the underling network. This issue is further emphasized in wireless network environment where network bandwidth is scarce resource. In this work, we focus our effort on developing performance model for wireless network. We collect packet trace from actually wireless network environment. We find that packet count process and bandwidth process in wireless environment exhibits long range property. We extract key performance parameters of the underlying network traffic. We develop an analytical model for buffer overflow probability and waiting time. We obtain the tail probability of the queueing system using Fractional Brown Motion (FBM). We represent average queuing delay from queue length model. Through our study based upon empirical data, it is found that our performance model well represent the physical characteristics of the IEEE 802.11b network traffic.

• Korean Security Journal
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• no.5
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• pp.109-130
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• 2002

As proceeding Munmin and Kukmin's government, it is to bring in regionalism of genernal public administration and police administration, specialization, efficiency issue, demand inventing of audit technique to meet this trends. Especially, according to supporting qualitative improvement of the audit, its environment faced that orienting performance audit emphasis on not the legality but the efficiency more systematic and scientific theory or technique. In order to attain police audit's efficiency through performance audit, this study discussed that scientific management techniques should be applied police audit. Accordingly, the primary purpose of this study is to apply public audit to scientific management technique, bring to light limits in public sector(especially, police sector). To be efficiency audit(namely, performance audit), 1) OR techniques are explained linear programming, network modeling, PERT/CPM, queuing matrix model, simulation, 2) Statistical analysis methods are argued delphi technique, data envelopment analysis(DEA), analytic hierarchical process(AHP), time series analysis models etc.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.12
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• pp.4389-4410
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• 2014

Network coding is a promising technology that increases system throughput by reducing the number of packet transmissions from the source node to the destination node in a saturated traffic scenario. Nevertheless, some packets can suffer from end-to-end delay, because of a queuing delay in an intermediate node waiting for other packets to be encoded with exclusive or (XOR). In this paper, we analyze the delay according to packet arrival rate and propose two network coding schemes, iXOR (Intelligent XOR) and oXOR (Optimal XOR) with Markov Decision Process (MDP). They reduce the average delay, even under an unsaturated traffic load, through the Holding-${\chi}$ strategy. In particular, we are interested in the unsaturated network scenario. The unsaturated network is more practical because, in a real wireless network, nodes do not always have packets waiting to be sent. Through analysis and extensive simulations, we show that iXOR and oXOR are better than the Distributed Coordination Function (DCF) without XOR (the general forwarding scheme) and XOR with DCF with respect to average delay as well as delivery ratio.

• Journal of Information Processing Systems
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• v.1 no.1 s.1
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• pp.62-69
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• 2005

This paper presents a queuing analysis model of a PC-based software router supporting IPv6-IPv4 translation for residential gateway. The proposed models are M/G/1/K or MMPP-2/G/1/K by arrival process of the software PC router. M/G/1/K is a model of normal traffic and MMPP-2/G/1/K is a model of burst traffic. In M/G/1/K, the arriving process is assumed to be a Poisson process, which is independent and identically distributed. In MMPP-2/G/1/K, the arriving process is assumed to be two-state Markov Modulated Poisson Process (MMPP) which is changed from one state to another state with intensity. The service time distribution is general distribution and the service discipline of the server is processor sharing. Also, the total number of packets that can be processed at one time is limited to K. We obtain performance metrics of PC-based software router for residential gateway such as system sojourn time blocking probability and throughput based on the proposed model. Compared to other models, our model is simpler and it is easier to estimate model parameters. Validation results show that the model estimates the performance of the target system.

• Journal of Intelligence and Information Systems
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• v.17 no.1
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• pp.1-16
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• 2011

The real-time ubiquitous environment is required to be able to process a series of sensor data within limited time. The whole sensor data processing consists of several phases : getting data out of sensor, acquiring context and responding to users. The ubiquitous computing middleware is aware of the context using the input sensor data and a series of data from database or knowledge-base, makes a decision suitable for the context and shows a response according to the decision. When the real-time ubiquitous environment gets a set of sensor data as its input, it needs to be able to estimate the delay-time of the sensor data considering the available resource and the priority of it for scheduling a series of sensor data. Also the sensor data of higher priority can stop the processing of proceeding sensor data. The research field for such a decision making is not yet vibrant. In this paper, we propose a queuing time computation algorithm for sensor data processing in real-time ubiquitous environment.

• Journal of KIISE:Software and Applications
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• v.34 no.8
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• pp.689-696
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• 2007

It is important issue for software architects to estimate performance of software in the early phase of the development process due to the need to verify non-functional requirements and estimation of performance in various stages of architectural design. In order to analyze performance of software, there are many approaches to translate software architecture represented by Unified Modeling Language, into analytical models. However, in the development of agent-based systems, these approaches ignore or simplify the crucial details of the underlying performance of the agent platform. In this paper, we propose performance prediction methodology for agent based system using formal semantic descriptions, and then, we transform the descriptions into queuing network model which model reflects performance of hardware and software platform. We prove the accuracy of proposed methodology using prototype implementation. The accuracy is summarized at 80%.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.45 no.4
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• pp.53-60
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• 2022

In a group-testing method, instead of testing a sample, for example, blood individually, a batch of samples are pooled and tested simultaneously. If the pooled test is positive (or defective), each sample is tested individually. However, if negative (or good), the test is terminated at one pooled test because all samples in the batch are negative. This paper considers a queueing system with a two-stage group-testing policy. Samples arrive at the system according to a Poisson process. The system has a single server which starts a two-stage group test in a batch whenever the number of samples in the system reaches exactly a predetermined size. In the first stage, samples are pooled and tested simultaneously. If the pooled test is negative, the test is terminated. However, if positive, the samples are divided into two equally sized subgroups and each subgroup is applied to a group test in the second stage, respectively. The server performs pooled tests and individual tests sequentially. The testing time of a sample and a batch follow general distributions, respectively. In this paper, we derive the steady-state probability generating function of the system size at an arbitrary time, applying a bulk queuing model. In addition, we present queuing performance metrics such as the offered load, output rate, allowable input rate, and mean waiting time. In numerical examples with various prevalence rates, we show that the second-stage group-testing system can be more efficient than a one-stage group-testing system or an individual-testing system in terms of the allowable input rates and the waiting time. The two-stage group-testing system considered in this paper is very simple, so it is expected to be applicable in the field of COVID-19.