• 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.

• Communications of the Korean Institute of Information Scientists and Engineers
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• v.5 no.2
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• pp.49-60
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• 1987

To decide on the queuing system of the optimum-sized bank window, data by means of simulation was reckoned. That is, by linking the average arrival rate and the average service rate with the exponential random number, customers' arrival time and service time was reckoned and simulation size optionally decided. By so doing, this paper is aimed at predicting the conditions of a bank, average arrival time, average waiting time, aveerage service time, average queuing length, servers' idle time, etd, and at preparing for a simulation model of the queuing system that can apply not only to the bank window box but also to all system under which queuing phenomena may arise.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.10 no.2
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• pp.22-34
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• 2011

This paper presents the investigation results of a research on how engineers can analyze the economic effect of the ETCS(Electronic Toll Collection System) installed to minimize the vehicle delays on freeway tollgates during toll payments. This research considered this economic effect to occur in the form of vehicle passing time reductions at the ETCS, and the multi-service queuing theory was applied to estimate these values. This research found: 1) When vehicles approaching tollgates show Poisson distribution and the service time of the ETCS shows Exponential distribution, the multi-service queuing theory would be applicable for estimating vehicle passing times at toll-gates, 2) Despite the ETCS placement, exit sections of tollgates give a greater reduction of vehicle passing times than entering sections due to more delays at conventional toll payments, and 3)The ETCS would not guarantee vehicle passing time reductions all the time, because in such a case as many vehicles were queuing at the ETCS, the total delay level for a toll gate would increase greatly. In addition, in order to examine the accuracy of the estimated vehicle passing values, this research compared the values from the multi-service queuing theory with the observed values from a set of field survey values at freeway toll-gates, and found that the two values were in a good agreement with a very low error range of 1-3 seconds per vehicle. Based on this result, the multi-service queuing theory was recommended for practice.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.6
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• pp.2450-2469
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• 2018

In this paper, we develop a spatiotemporal model to analysis of cellular user in underlay D2D communication by using stochastic geometry and queuing theory. Firstly, by exploring stochastic geometry to model the user locations, we derive the probability that the SINR of cellular user in a predefined interval, which constrains the corresponding transmission rate of cellular user. Secondly, in contrast to the previous studies with full traffic models, we employ queueing theory to evaluate the performance parameters of dynamic traffic model and formulate the cellular user transmission mechanism as a M/G/1 queuing model. In the derivation, Embedded Markov chain is introduced to depict the stationary distribution of cellular user queue status. Thirdly, the expressions of performance metrics in terms of mean queue length, mean throughput, mean delay and mean dropping probability are obtained, respectively. Simulation results show the validity and rationality of the theoretical analysis under different channel conditions.

• Industrial Engineering and Management Systems
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• v.15 no.4
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• pp.354-363
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• 2016

Due to uncertain environment, various parameters such as price, queuing length, warranty, and so on influence on inventory models. In this paper, an inventory-queuing-pricing problem with continuous review inventory control policy and batch arrival queuing approach, is presented. To best of our knowledge, (I) demand function is stochastic and price dependent; (II) due to the uncertainty in real-world situations, a fuzzy programming approach is applied. Therefore, the presented model with goal of maximizing total profit of system analyzes the price and order quantity decision variables. Since the proposed model belongs to NP-hard problems, Pareto-based approaches based on non-dominated ranking and sorting genetic algorithm are proposed and justified to solve the model. Several numerical illustrations are generated to demonstrate the model validity and algorithms performance. The results showed the applicability and robustness of the proposed soft-computing-based approaches to analyze the problem.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2017.11a
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• pp.27-29
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• 2017

Container terminals in Northern Vietnam have recorded an impressive development in recent years. This development, however, also raises a fierce competition among local container terminals to attract customers. Beside the handling charges, the vessels' waiting cost is also an important factor that drive the opinion of users in choosing appropriate terminal. This research plans to estimate the waiting cost in different container terminals in Northern Vietnam by building regression equation that describe the relationship between the rate of throughput/capacity and waiting cost/TEU. Queuing theory with the application of Poisson distibution is used to estimate the waiting time of arrival vessels and uncertainty theory is applied to estimate the vessel's daily expenses. Previous studies suggested two different formation of the equation and according to the research results, cubic equation is more suitable in the given case. The research results are also useful for further research which require calculation of waiting cost per TEU in each container terminal in Northern Vietnam.

• 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.

• 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.

• Journal of Communications and Networks
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• v.13 no.3
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• pp.286-297
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• 2011

A novel converged optical network unit (ONU)-base station (BS) architecture has been contemplated for next-generation optical-wireless networks. It has been demonstrated through high quality studies that data traffic carried by both wired and wireless networks exhibit self-similar and long range dependent characteristics; attributes that classical teletraffic theory based on simplistic Poisson models fail to capture. Therefore, in order to apprehend the proposed converged architecture and to reinforce the provisioning of tightly bound quality of service (QoS) parameters to end-users, we substantiate the analysis of the QoS behavior of the ONU-BS under self-similar and long range dependent traffic conditions using custom queuing which is a common queuing discipline. This paper extends our previous work on priority queuing and brings novelty in terms of presenting performance analysis of the converged ONU-BS under realistic traffic load conditions. Further, the presented analysis can be used as a network planning and optimization tool to select the most robust and appropriate queuing discipline for the ONU-BS relevant to the QoS requirements of different applications.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.2
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• pp.61-67
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• 2017

In this paper, an adaptive MAC technique for various underwater environment with narrow-bandwidth and low transmission speed was proposed. In previously published Underwater Packet Flow Control (UPFC) technique, three transmission types (normal, block and parallel transmission) had been proposed using the number of transmission and transmission time. In addition to the UPFC, the proposed technique is an improved version of UPFC having more effective queuing technique for merge transmission. A mathematical model of the proposed queuing theory was constructed and its increased efficiency per unit transmission number was also verified based on simulations.