Workflow-Oriented the Optimal Path Web Services in Multi-Level Road Network

被引:0
|
作者
Chen, Yumin [1 ]
Gong, Jianya [2 ]
Cao, Haitao [2 ]
Gui, Zhipeng [2 ]
机构
[1] Wuhan Univ, Sch Resource & Environm Sci, Wuhan 430072, Peoples R China
[2] Wuhan Univ, State Key Lab Informat Engn Surveying Mapping & R, Wuhan, Peoples R China
关键词
the optimal path web services; multi-level road network; workflow-oriented;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Usually, a typical city road network is very huge, including thousands upon thousands of nodes. If several cities are considered, even countrywide or larger area, the classical algorithm is very difficult to get a correct result. To solve this problem effectively, when a mass of data is given, distributed multi-level road network data is considered. It builds pyramid-liked data model, calculates the optimal path analysis in multiple layers, and then conflates the final results by sub-result coming from multi-levels. With development of Web Service technology and Internet network, it provided necessary preparation for data sharing and interoperability of distributed information. So it provides technique support for a dynamical building of pyramid-liked multi-level road network data model and an optimal path service. Workflow technology can effectively build all data sharing web services and functional web services into one executable service chain. Using self-developed workflow software will combine related web services into an abstract service chain. The abstract service chain is mapped into BPEL standards service chain. Finally, the Active BPEL workflow engine will be used to implement the service chain, and the results will be sent to the client. The service application proves that the optimal path service on multi-level road network is feasible and efficient to deal with large area optimal path analysis problem.
引用
收藏
页码:439 / +
页数:2
相关论文
共 50 条
  • [31] Workflow composition of service level agreements for web services
    Blake, M. Brian
    Cummings, David J.
    Bansal, Ajay
    Bansal, Srividya Kona
    DECISION SUPPORT SYSTEMS, 2012, 53 (01) : 234 - 244
  • [32] Optimal network intrusion detection assignment in multi-level IoT systems
    Dao, Thi-Nga
    Van Le, Duc
    Tran, Xuan Nam
    COMPUTER NETWORKS, 2023, 232
  • [33] The multi-level perspective and micromobility services
    Medina-Molina, Cayetano
    Perez-Macias, Noemi
    Gismera-Tierno, Laura
    JOURNAL OF INNOVATION & KNOWLEDGE, 2022, 7 (02):
  • [34] Efficient route plan algorithm based on multi-level road network strategy
    Zhong H.
    Zhang M.
    Shi Y.
    Cai W.
    Xinan Jiaotong Daxue Xuebao/Journal of Southwest Jiaotong University, 2011, 46 (04): : 645 - 650
  • [35] A service-oriented architecture framework for multi-level failure detection services in grid
    Haijun Zhao
    Yan Ma
    Xiaohong Huang
    Yujie Su
    IC-BNMT 2007: PROCEEDINGS OF 2007 INTERNATIONAL CONFERENCE ON BROADBAND NETWORK & MULTIMEDIA TECHNOLOGY, 2007, : 312 - 316
  • [36] Road Recognition Based on Multi-scale Convolutional Network with Multi-level Feature Fusion
    Li, Ye
    Guo, Lili
    Xu, Lele
    Wang, Xianfeng
    Jin, Shan
    TENTH INTERNATIONAL CONFERENCE ON GRAPHICS AND IMAGE PROCESSING (ICGIP 2018), 2019, 11069
  • [37] Multi-scale features fused network with multi-level supervised path for crowd counting
    Wang, Yongjie
    Zhang, Wei
    Huang, Dongxiao
    Liu, Yanyan
    Zhu, Jianghua
    EXPERT SYSTEMS WITH APPLICATIONS, 2022, 200
  • [38] Towards Optimal Multi-Level Checkpointing
    Benoit, Anne
    Cavelan, Aurelien
    Le Fevre, Valentin
    Robert, Yves
    Sun, Hongyang
    IEEE TRANSACTIONS ON COMPUTERS, 2017, 66 (07) : 1212 - 1226
  • [39] Multi-level Architecture on Web Services Based Policy Domain Use Cases Simulator
    Aizstrauts, Artis
    Ginters, Egils
    Lauberte, Ieva
    Piera Eroles, Miquel Angel
    ENTERPRISE AND ORGANIZATIONAL MODELING AND SIMULATION, EOMAS 2013, 2013, 153 : 130 - 145
  • [40] Multi-Level Memory for Task Oriented Dialogs
    Reddy, Revanth
    Contractor, Danish
    Raghu, Dinesh
    Joshi, Sachindra
    2019 CONFERENCE OF THE NORTH AMERICAN CHAPTER OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS: HUMAN LANGUAGE TECHNOLOGIES (NAACL HLT 2019), VOL. 1, 2019, : 3744 - 3754