• JSTS:Journal of Semiconductor Technology and Science
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• v.15 no.5
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• pp.570-576
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• 2015

Existing flash storage devices such as universal flash storage and solid state disk support command queuing to improve storage I/O bandwidth. Command queuing allows multiple read/write requests to be pending in a device queue. Because multi-channel and multi-way architecture of flash storage devices can handle multiple requests simultaneously, command queuing is an indispensable technique for utilizing parallel architecture. However, command queuing can be harmful to the latency of fsync system call, which is critical to application responsiveness. We propose a dynamic queue depth adaptation technique, which reduces the queue depth if user application is expected to send fsync calls. Experiments show that the proposed technique reduces the fsync latency by 79% on average compared to the original scheme.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.47 no.3
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• pp.1-7
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• 2024

In an influential paper, Choi and Kim (2010) derived waiting times in an M/M/1 queuing model under net neurality and under prioritization. In this short paper, we argue that the waiting times of content transmission that Choi and Kim (2010) derived by using the M/M/1 gueuing model under the non-preemptive priority rule are miscalculated. We provide corrected waiting times in the M/M/1 queuing model in the prioritization case. We also show that this correction does not affect their main results on the delay time and the incentive to invest in the network capacity qualitatively.

• Journal of Korean Institute of Industrial Engineers
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• v.17 no.1
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• pp.59-73
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• 1991

In this paper, how to evaluate the assembly system was studied. The traction machine(TRM/C) is a kind of medium sized small quantity product. This work was performed on restriction of satisfying the customer's demand by simulating on the criteria of the queuing quantity in production system, the effectiveness of assembly machine and the average time spent on assembling. The problems about assembling were grasped through the analysis of products and process. The outputs of simulations that used SIMAN on four alternatives were evaluated on the basis of the average queuing quantity, the line effectiveness, the assembly time of a product and the production capacity.

• The Journal of Information Systems
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• v.29 no.2
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• pp.131-147
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• 2020

Purpose The purpose of this study is to develop intelligent vehicle parking distribution system based on LoRa network at the circumstance of traffic congestion during cultural festival in a local city. This paper proposes a parking dispatch and distribution system using a Q-learning algorithm to rapidly disperse traffics that increases suddenly because of in-bound traffics from the outside of a city in the real-time base as well as to increase parking probability in a parking lot which is widely located in a city. Design/methodology/approach The system get information on realtime-base from the sensor network of IoT (LoRa network). It will contribute to solve the sudden increase in traffic and parking bottlenecks during local cultural festival. We applied the simulation system with Queuing model to the Yudeung Festival in Jinju, Korea. We proposed a Q-learning algorithm that could change the learning policy by setting the acceptability value of each parking lot as a threshold from the Jinju highway IC (Interchange) to the 7 parking lots. LoRa Network platform supports to browse parking resource information to each vehicle in realtime. The system updates Q-table periodically using Q-learning algorithm as soon as get information from parking lots. The Queuing Theory with Poisson arrival distribution is used to get probability distribution function. The Dijkstra algorithm is used to find the shortest distance. Findings This paper suggest a simulation test to verify the efficiency of Q-learning algorithm at the circumstance of high traffic jam in a city during local festival. As a result of the simulation, the proposed algorithm performed well even when each parking lot was somewhat saturated. When an intelligent learning system such as an O-learning algorithm is applied, it is possible to more effectively distribute the vehicle to a lot with a high parking probability when the vehicle inflow from the outside rapidly increases at a specific time, such as a local city cultural festival.

• Proceedings of the IEEK Conference
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• summer
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• pp.269-273
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• 2004

This paper presents a comparative performance analysis of a network accelerator model based on M/M/l queuing system. It assumes the Poisson distribution as its input traffic load. The decoding delay is employed as a performance analysis measure. Simulation results based on the proposed model show only $15\%$ differences with respect to actual measurements on field traffic for BCM5820 accelerator device. The performance analysis model provides with reasonable hardware structure of network servers, and can be used to span design spaces statistically.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.41 no.4
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• pp.17-24
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• 2004

Call blocking probabilities of streaming data service in CDMA system with access point(AP) of WLAN are analyzed for different cell geometry of base station and AP and queuing is modeled. The considered system leads to successful handoffs between the APs of WLAN. Blocking probabilities are enumerated as a function for ratio of base station and AP sizes, their locations and the number of buffer in the queue. Results show that blocking probability is not influenced by base station and AP locations but mainly by ratio of their sizes. For CDMA system of radius 100m, 5 buffers in the queue and 7㏈ noise rise(NR), in order to obtain 1% call blocking probability, a cell with hot spot of radius 20m has more 0.6Erlang than that of radius 60m.

• Journal of KIISE:Information Networking
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• v.30 no.3
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• pp.416-423
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• 2003

This paper proposes a continuous-time queuing model of a shared-buffer packet switch and an approximate algorithm. N arrival processes have heterogeneous busty traffic characteristics. The arrival processes are modeled by Coxian distribution with order 2 that is equivalent to Interruped Poisson Process. The service time is modeled by Erlang distribution with r stages. First the approximate algorithm performs the aggregation of N arrival processes as a single state variable. Next the algorithm discompose the queuing system into N subsystems which are represented by aggregated state variables. And the balance equations based on these aggregated state variables are solved for by iterative method. Finally the algorithm is validated by comparing the results with those of simulation.

• Journal of applied mathematics & informatics
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• v.41 no.4
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• pp.861-868
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• 2023

Nonlinear network creates complex homotopy structural communication in wireless network medium because of complex distribution approach. Due to this multicast topological connection structure, the queuing probability was non regular principles to create routing structures. To resolve this problem, we propose a Co-cluster homotopy queuing model (Co-CHQT) for Nonlinear Algebraic Topological Structure (NLTS-) for improving poison distribution network communication. Initially this collects the routing propagation based on Nonlinear Distance Theory (NLDT) to estimate the nearest neighbor network nodes undernon linear at x_(a,b)→ax²+bx² = c. Then Quillen Network Decomposition Theorem (QNDT) was applied to sustain the non-regular routing propagation to create cluster path. Each cluster be form with co variance structure based on Two unicast 2(n+1)-Z2(n+1)-Z network. Based on the poison distribution theory X_(a,b) ≠ µ(C), at number of distribution routing strategies weights are estimated based on node response rate. Deriving shorte;'l/st path from behavioral of the node response, Hilbert -Krylov subspace clustering estimates the Cluster Head (CH) to the routing head. This solves the approximation routing strategy from the nonlinear communication depending on Max- equivalence theory (Max-T). This proposed system improves communication to construction topological cluster based on optimized level to produce better performance in distance theory, throughput latency in non-variation delay tolerant.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.4 no.3
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• pp.549-555
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• 2000

We propose an approximate algorithm to analyze the queuing system with n bursty and heterogeneous arrival processes. Each input process is modeled by Interrupted Bernoulli Process(IBP). We approximate N arrival processes by a single state variable and subsequently simplify the transition probability matrix of the Markov chain associated with these N arrival processes. Using this single state variable of arrival processes, we describe the state of the queuing system and analyze the system numerically with the reduced transition probability matrix. We compute the queue length distribution, the delay distribution, and the loss probability. Comparisons with simulation data show that the approximation algorithm has a good accuracy.

• Journal of the Korea Society of Computer and Information
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• v.10 no.4 s.36
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• pp.221-228
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• 2005

Data storage was thought to be inside of or next to server cases but advances in networking technology make the storage system to be located far away from the main computer. In Internet era with explosive data increases, balanced development of storage and transmission systems is required. SAN(Storage Area Network) and NAS(Network Attached Storage) reflect these requirements. It is important to know the capacity and limit of the complex storage network system to got the optimal performance from it. The capacity data is used for performance tuning and making purchasing decision of storage. This paper suggests an analytic model of storage network system as queuing network and proves the model though simulation model.