• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.1
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• pp.146-170
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• 2017

Joint channel assignment and routing is a well-known problem in multi-radio wireless mesh networks for which optimal configurations is required to optimize the overall throughput and fairness. However, other objectives need to be considered in order to provide a high quality service to network users when it deployed with high traffic dynamic. In this paper, we propose a re-configuration optimization model that optimizes the network throughput in addition to reducing the disruption to the mesh clients' traffic due to the re-configuration process. In this multi-objective optimization model, four objective functions are proposed to be minimized namely maximum link-channel utilization, network average contention, channel re-assignment cost, and re-routing cost. The latter two objectives focus on reducing the re-configuration overhead. This is to reduce the amount of disrupted traffic due to the channel switching and path re-routing resulted from applying the new configuration. In order to adapt to traffic dynamics in the network which might be caused by many factors i.e. users' mobility, a centralized heuristic re-configuration algorithm called State-Aware Joint Routing and Channel Assignment (SA-JRCA) is proposed in this research based on our re-configuration model. The proposed algorithm re-assigns channels to radios and re-configures flows' routes with aim of achieving a tradeoff between maximizing the network throughput and minimizing the re-configuration overhead. The ns-2 simulator is used as simulation tool and various metrics are evaluated. These metrics include channel-link utilization, channel re-assignment cost, re-routing cost, throughput, and delay. Simulation results show the good performance of SA-JRCA in term of packet delivery ratio, aggregated throughput and re-configuration overhead. It also shows higher stability to the traffic variation in comparison with other compared algorithms which suffer from performance degradation when high traffic dynamics is applied.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.8A
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• pp.1169-1176
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• 2000

In this paper, label assignment schemes considering the IP flow model for the efficient MPLS traffic engineering are proposed and evaluated. Based on the IP flow model, the IP flows are classified into transient flows and base flows. Base flows, which last for a long time, transmit data in high bit rate, and be composed of many packets, have good implications for the MPLS traffic engineering, because they usually cause network congestion. To make use of base flows for the MPLS traffic engineering, we propose two base flow classifiers and label assignment schemes where transient flows are allocated to the default LSPs and base flows to explicit LSPs. Proposed schemes are based on the traffic-driven label triggering method combined with a routing tabel. The first base flow classifier uses both flow size in packet counts and routing entries, and the other one, extending the dynamic X/Y flow classifier, is based on a cut-through ratio. Proposed schemes are shown to minimize the number of labels, not degrading the total cut-through ratio.

• Journal of Korean Society of Transportation
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• v.21 no.6
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• pp.77-88
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• 2003

This paper proposes a solution algorithm for solving a multi-class analytical DTA model. In the DTA model, three traveler classes are classified according to different assumptions of traveler's route choice behavior: including fixed route, Stochastic Dynamic User Optimum(SDUO), and Dynamic User Optimum(DUO). To solve this DTA model, variables of link flow and exit flow are represented solely by inflow. The resulting Linear Program(LP) subproblem in the inner iteration is solved as a typical time-dependent shortest route problem over a physical network. Accordingly, the required time-space network expansion in solving DTA models is no longer needed.

• Journal of Korean Society of Transportation
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• v.22 no.7 s.78
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• pp.91-98
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• 2004

This study focuses on the development of dynamic assignment for evaluation and application for dynamic route guidance strategy. Travelers are classified according to information contents which they received pre/on trip. The first group have no traffic information, so they travel with fixed route. The second group have real-time shortest path and travel according to it. The last group have car navigation system or individual method(cellular phone, PDA-two way communication available) for traffic information on trip. And then they are assigned in accordance with the proposed multiclass dynamic assignment model. At this time the last group is gotten under control with DFS(decentralized feedback strategy). In use of this Process we expect that various traffic information strategy can be tested and also be the key factor for success of ITS, location of VMS(variable message sign), cycle of information, area of traffic information, etc).

• Journal of Korean Society of Transportation
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• v.20 no.3
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• pp.149-158
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• 2002

For the purpose of preciously describing real time traffic pattern in urban road network, dynamic network loading(DNL) models able to simulate traffic behavior are required. A number of different methods are available, including macroscopic, microscopic dynamic network models, as well as analytical model. Equivalency minimization problem and Variation inequality problem are the analytical models, which include explicit mathematical travel cost function for describing traffic behaviors on the network. While microscopic simulation models move vehicles according to behavioral car-following and cell-transmission. However, DNL models embedding such travel time function have some limitations ; analytical model has lacking of describing traffic characteristics such as relations between flow and speed, between speed and density Microscopic simulation models are the most detailed and realistic, but they are difficult to calibrate and may not be the most practical tools for large-scale networks. To cope with such problems, this paper develops a new DNL model appropriate for dynamic traffic assignment(DTA), The model is combined with vertical queue model representing vehicles as vertical queues at the end of links. In order to compare and to assess the model, we use a contrived example network. From the numerical results, we found that the DNL model presented in the paper were able to describe traffic characteristics with reasonable amount of computing time. The model also showed good relationship between travel time and traffic flow and expressed the feature of backward turn at near capacity.

• Journal of Korean Society of Transportation
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• v.15 no.2
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• pp.51-66
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• 1997

실시간 변화하는 교통상황을 파악하고 교통혼잡을 완화시키려는 각종 교통정책들을 개발하고 평가하기 위하여 동적 통행배정모형에 대한 연구가 지속되고 있으며 상당한 성과 를 이루고 있다. 그러나 이론적인 어려움과 계산량과 과다로 기존의 모형들은 대부분 단순 가로망을 대상으로 적용되어 왔으며 대규모 가로망에 적용하는 데는 상당한 어려움을 겪고 있다. 본 연구의 목적은 실제 가로망에 쉽게 적용할 수 있는 휴리스틱 동적 통행배정모형을 개발하고 이를 해석할 수 있는 알고리즘을 개발하는 데 있다. 개발되는 모형은 변동부등식 (variational inequality)으로 구축되며 알고리즘은 휴리스틱 알고리즘(heuristic disagonalized algorithm)을 개발한다. 예제 가로망을 대상으로 개발된 모형을 평가하며 도출된 해가 Wrdrop의 균형해(equilibrium)임을 보인다.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1995.04a
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• pp.724-728
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• 1995

A new dynamic channel assignment (DCA) algorithm with rearrangement for cellular mobile communication systems is suggested. Our DCA algorithm is both traffic and interference adaptive, which is based on the mathematical formulation of the maximum packing under a realistic propagation model. In developing the algorithm, we adopt the Lagrangean relaxation technique that has been successfully used in the area of mathematical programming. Computational experiments of the algorithm reveal quite encouraging results. Although our algorithm primarily focuses on microcellular systems, it can be effectively applied to conventional cellular systems under highly nonuniform traffic distributions and interference conditions.

• Journal of Korean Society of Transportation
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• v.20 no.1
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• pp.101-110
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• 2002

This study first explains general features of traffic assignment models and network loading methods, and investigates the relationship between them. Then it introduces a dynamic network loading method, which accounts far time variable additionally. First of all, this study suggests that it is important to consider some requirements for the dynamic network loading, such as causality, FIFO(First-In-First-Out) discipline, the flow propagation, and the flow conservation. The details of dynamic network loafing methods are explained in the form of algorithm, and numerical examples are shown in the test network by adopting deterministic queuing model for a link Performance function.

• Journal of Korean Society of Transportation
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• v.17 no.1
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• pp.141-157
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• 1999

This paper first reviews current practices of traveler information providing and provides some perspectives regarding the possible near term milestones in traveler information providing. Then, reviews of four types of prediction models: 1) dynamic traffic assignment (DTA) model; 2) statistical model; 3) simulation model; and 4) heuristic model are described in the sense that various prediction models are needed to support providing predictive traveler information in the near future. Next, the functional requirements and capabilities of the four types of prediction models are discussed and summarized along with some advantages and disadvantages of these models with reference to short-term travel time prediction. Furthermore, a comprehensive prediction procedure, which combines the four types of prediction models, is presented, together with the data requirements for each type of prediction model.

• Journal of Korean Society of Transportation
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• v.29 no.1
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• pp.71-79
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• 2011

Traditionally, a dynamic network model is considered as a tool for solving real-time traffic problems. One of useful and practical ways of using such models is to use it to produce and disseminate forecast travel time information so that the travelers can switch their routes from congested to less-congested or uncongested, which can enhance the performance of the network. This approach seems to be promising when the traffic congestion is severe, especially when sudden incidents happen. A consideration that should be given in implementing this method is that travel time information may affect the future traffic condition itself, creating undesirable side effects such as the over-reaction problem. Furthermore incorrect forecast travel time can make the information unreliable. In this paper, a network-wide travel time prediction model under incidents is developed. The model assumes that all drivers have access to detailed traffic information through personalized in-vehicle devices such as car navigation systems. Drivers are assumed to make their own travel choice based on the travel time information provided. A route-based stochastic variational inequality is formulated, which is used as a basic model for the travel time prediction. A diversion function is introduced to account for the motorists' willingness to divert. An inverse function of the diversion curve is derived to develop a variational inequality formulation for the travel time prediction model. Computational results illustrate the characteristics of the proposed model.