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Virtual network construction with k-shortest path algorithm and optimization problems for robust physical networks

INTERNATIONAL JOURNAL OF COMMUNICATION SYSTEMS 2017年第1期30卷 1-21页

作者： Urayama, Yasuhiro Tachibana, Takuji Univ Fukui Grad Sch Engn 3-9-1 Bunkyo Fukui 9108507 Japan

In network virtualization, it has been considered that virtual networks are constructed over a physical network where conventional data transmission services have been utilized. Here, virtual networks have to be constructed while keeping qualities of the conventional services. In this paper, we propose a new virtual network construction in order to construct many virtual networks while keeping the robustness of a physical network by using network resources effectively. The proposed method consists of three processes: k-shortest path algorithm and Prim's minimum spanning tree algorithm, path splitting, and path migration. In the proposed method, at first, multiple topologies are designed by using the k-shortest path algorithm and the Prim's MST algorithm according to the user's request. After the topology design is completed, an admission control with network robustness of the physical network is performed. Then, if one of the designed topologies can satisfy the construction conditions, a virtual network is constructed and provided with the user. Otherwise, the path splitting and path migration are performed. Here, the path splitting is utilized to design another topology of a virtual network and path migration is used to change the topologies of the virtual networks that have already been constructed. These processes are formulated as optimization problems and those are processed by solving the optimization problems. In numerical examples, we show that our proposed method can construct a higher number of virtual networks while keeping the robustness of a physical network by comparing with the conventional method where only the kou-Markowsky-Berman algorithm is used. Copyright (C) 2015 John Wiley & Sons, Ltd.

关键词： network virtualization robustness k-shortest path algorithm path splitting path migration optimization problem

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Performance optimization of intelligent optical networks by multiple alternate routes based on the k-shortest path algorithm

Performance optimization of intelligent optical networks by ...

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Conference on Network Architectures, Management, and Applications IV, Pts 1 & 2

作者： Cu, Xinyou Zheng, Xiaoping Zhang, Hanyi Li, Yanhe Guo, Yili Tsinghua Univ Dept Elect Engn Beijing 100084 Peoples R China

ISBN: (纸本)081946449X

Blocking probability is one of the key factors to evaluate the routing and wavelength algorithms for intelligent optical network. Two kinds of Dynamic k-shortest path (DkSP) algorithms were designed. One is based on Linear Link Weight Function (LW) and the other is based on Piecewise Linear Link Weight Function (PLW). It was found that the two kinds of DkSP can significantly decrease the blocking probability of optical network comparing to the static kSP for the same number of alternate routes. Compared to routing with LW, the coefficient of PLW has larger effect on the blocking probability of optical network when the number of alternate route is small, but the effect is weakened with the increase of the number of alternate route. As far as the two kinds of DkSP algorithms are concerned, DkSP with PLW has some advantage over DkSP with LW on decreasing the blocking probability. It was also found that the optimized performance can almost be got by DkSP with only 2-4 alternate routes for NSFNET.

关键词： Routing and Wavelength Assignment k-shortest path algorithm Dynamic k-shortest path algorithm Linear Link Weight Function Piecewise Linear Link Weight Function Blocking Probability

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Research on path selection and flow scheduling of time-sensitive networks for power substations

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ENERGY REPORTS 2023年 9卷 1042-1048页

作者： Xu, Jiangpei Wang, Jin Gao, Sihang Liu, Chang Wang, Jie Wei, Min Zhou, Liang Tian, Li State Grid Hubei Elect Power Res Inst Wuhan Hubei Peoples R China Chongqing Univ Posts & Telecommun Automat Coll Lab Ind Internet Things Chongqing Peoples R China

In view of the problem that the flow of intelligent substation traffic scheduling increases, resulting in the transmission delay also increases, this paper proposed a joint optimization method of Time Sensitive Network (TSN) path selection and scheduling, which combines the resource sensing k-shortest path algorithm (kPA) path selection algorithm and the constraint based gating method. This method can select an optimal transmission path for TT flows and plan the transmission path for non TT flows. Based on the scheduling mechanism of TSN, constraints and optimization objective functions are established, and a gating scheduling method based on constraints is proposed. Finally, the test and verification platform of the scheme is designed and built. Through the test and verification platform, the data stream transmission delay and delay jitter of the scheme are analyzed, and the algorithms are compared and analyzed from the aspects of running time and schedulability. With the continuous evolution of the follow-up TSN technology and the in-depth promotion of the power industry, more and more TSN key technologies will be applied to the smart grid.& COPY;2023 Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://***/licenses/by-nc-nd/4.0/).

关键词： Intelligent substation Time Sensitive Network k-shortest path algorithm Traffic scheduling TT flow Non TT flow

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Research on the Method of Calculating Train Congestion Index Based on the Automatic Fare Collection Data 3rd

Research on the Method of Calculating Train Congestion Index...

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3rd International Conference on Electrical Engineering and Information Technologies for Rail Transportation (EITRT)

作者： Zhang, Wenxuan Tang, Jinjin Beijing Jiaotong Univ Sch Traff & Transportat Beijing Peoples R China

ISBN: (纸本)9789811079863;9789811079856

With the increasing operating mileage of the urban railway transit, the traffic volume of the urban railway network has risen sharply. In order to enhance the performance and safety of the urban railway transit, the research on the train congestion index is imminent. In this paper, firstly, the definition of congestion index is proposed, and the congestion degree model is formulated. Secondly, the real-time congestion degree of train lines is obtained by using the algorithm based on the spatial and temporal k-shortest path. Finally, the train congestion of Xi'an subway is analyzed and calculated by the model based on the data of passengers' transportation cards and the process consumes just 3 min. Comparing with the actual results, we come to the conclusion that the train congestion model and space-time k-shortest path algorithm are correct and feasible, which can provide constructive suggestions on the operation and management of the urban railway network and the flow limitation of the station.

关键词： Passenger card data Train congestion index k-shortest path algorithm Urban rail transit

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Multi-path Acquiring Methods Based on Multi-population Parallel Genetic algorithm

Multi-Path Acquiring Methods Based on Multi-population Paral...

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27th Chinese Control Conference

作者： Wang Zhengwu Li Chunyuan Changsha Univ Sci &Technol Sch Traff & Transportat Engn Changsha 410076 Hunan Peoples R China

ISBN: (纸本)9787900719706

To avoid the negative effect of guidance and to decrease congestion shifting caused because the drivers choose the optimum path simultaneously, more reasonable paths should be recommended, but there is no quick and effective algorithm to seek the k-shortest path. Genetic algorithm, characterized by overall optimization and potential parallel, is suitable for k-shortest path seeking. When the ordered nodes are applied, premature convergence and low searching efficiency at later stage of evolutionary often appear because a large number of invalid paths are produced during the genetic operation, and the path is more blindly generated. This paper will improve the algorithm in two ways: firstly, convergence speed is improved by the introduction of multi-population parallel algorithm which can maintain the population diversities, prevent premature convergence and improve later searching efficiency;secondly, a new code method is used to reduce algorithm complexity. The code method based on the turn actions is adopted to decrease the invalid path number during the genetic operation while the loop punishment factor is introduced in the fitness calculation to avoid the operations of eliminating loops. Numerical research shows that the improved algorithm has the advantages on fast convergence and high searching efficiency.

关键词： Multi-population parallel genetic algorithm k-shortest path algorithm Multi-route guidance Migration

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Finding routes in a public transport network. A case study 19

Finding routes in a public transport network. A case study

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19th International Conference on Methods and Models in Automation and Robotics (MMAR)

作者： Olczyk, Adrian Galuszka, Adam Silesian Tech Univ Inst Automat Control PL-44100 Gliwice Poland

ISBN: (纸本)9781479950812

There is a need for reliable and trustworthy public transport planner services. Mass transits are trying to solve problems as traffic jams or increasing pollution in densely populated city agglomerations. Passengers are looking for travel information on-line and companies providing public transport solutions often struggle with providing modern trip planner platforms. We address this problem by providing simple and easy to implement solution for shortest paths computation in public transport network of any size. In first part of the paper we present our approach to building time-expanded graph model of public transportation network. We use a structure with multiple vertices within one stop identified by triple (stop, time, line) and edges with constant travel times. Second part introduces k-shortest paths algorithm for created graph. We provide step by step explanation along with code samples. Average algorithm response time is around 1.5s for a public transport network of the size over 2800 stops. This is accepted query time for a web application. None additional speed-up techniques has been used to keep implementation and explanations simple and leaving room for further improvements. algorithm has been successfully tested in Upper Silesian Industrial District (GOP) in cooperation with main public transport provider in the area (kZk GOP). This real instance is the biggest one in Poland and contains 370 lines and over 2800 stops.

关键词： graph theory public transport Upper Silesian Industrial District k-shortest path algorithm mass transit public transport planner service public transportation network time-expanded graph model travel information trip planner platform Data structures Educational institutions Mobile communication Planning Reliability Routing Transportation Travel information Transport networks Public Transit Mass transit public transport network Educational institutions Data structures mobile communication shortest path algorithms Graph theory Network routing transport FINDINGS

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A Heuristic algorithm to Study the Influence of Road Preference on Network Capacity

A Heuristic Algorithm to Study the Influence of Road Prefere...

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4th International Conference on Manufacturing Science and Engineering (ICMSE 2013)

作者： Yang Weidong Fan Dongtao Bai Hua Jiangsu provincial communications planning and design institute co. ltd.

ISBN: (纸本)9783037856932

In this study, an algorithm was proposed to study the influence of road preference on the network capacity in urban transportation system. Of particular interest is to model the discrete choice model with respect to the road preference and the travel time. New formulations are presented in terms of the multi-objective road preference modeling and the travel time modeling for multi vehicle types. Compared with existing techniques, an improved heuristic method is put forward to explore the network capacity.

关键词： heuristic algorithm road preference network capacity k-shortest path algorithm

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Stochastic traffic assignment of mixed electric vehicle and gasoline vehicle flow with path distance constraints

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Transportation Research Procedia 2017年 21卷 65-78页

作者： Wentao Jing Inhi kim Mohsen Ramezani Zhiyuan Liu Institute of Transport Studies Department of Civil Engineering Monash University Clayton Victoria 3800 Australia School of Transportation Southeast University Nanjing China

This paper addresses a general stochastic user equilibrium (SUE) traffic assignment problem (TAP) for transport networks with electric vehicles (EV), where EV paths are restricted by the EV driving range limits. A minimization model for path-constrained SUE is first proposed as an extension of path-constrained deterministic user equilibrium (DUE) TAP, which also extends the existing general SUE models with link-based constraints to path-based constraints. The resulting SUE model and solution algorithm can be used for other conditions with similar path-based constraints. The equilibrium conditions reveal that any path cost in the network is the sum of corresponding link costs and a path specific out-of-range penalty term, while path out-of-range term should equal to zero to ensure feasible flows. We develop a modified method of successive averages (MSA) with a predetermined step size sequence where both multinomial logit and multinomial probit based loading procedure are applied to solve the TAP. The suggested methods incorporate k-shortest paths algorithm to generate the path set on a need basis. Finally, two numerical examples are presented to verify the proposed model and solution algorithms.

关键词： Traffic assignment stochastic user equilibrium path distance constraints k-shortest path algorithm Multinomial Logit Multinomial Probit

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