Versioning of Network Models in a Multiuser Environment

  • Authors:
  • Petko Bakalov;Erik Hoel;Sudhakar Menon;Vassilis J. Tsotras

  • Affiliations:
  • Environmental Systems Research Institute, Redlands, USA 92373;Environmental Systems Research Institute, Redlands, USA 92373;Environmental Systems Research Institute, Redlands, USA 92373;University of California, Riverside, USA 92507

  • Venue:
  • SSTD '09 Proceedings of the 11th International Symposium on Advances in Spatial and Temporal Databases
  • Year:
  • 2009

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Abstract

The standard database mechanisms for concurrency control, which include transactions and locking protocols, do not provide the support needed for updating complex geographic data in a multiuser environment. The preferred method to resolve conflicts in GIS systems is to encapsulate the modifications generated by the end users through the use of multiple versions. Multiuser (or versioned) geographic databases allow users to operate as though they have full access to the entire dataset. Instead of relying upon row locking, versioned databases allow multiple users to simultaneously edit the same row. They implement a model for conflict detection and resolution where the first to commit the change wins by default (though clients can manually intervene and select the latter change as the winner). Network models are frequently used as a mechanism to describe the connectivity information between spatial features in many emerging GIS applications. Supporting networks within the context of a versioned database imposes additional requirements --- the complex network model must retain integrity irrespective of the sequence of simultaneous edits by various clients. In this paper, we review our network model and discuss the enhancements necessary to maintaining topological network integrity in this complex environment. Our solution is based on the notion of dirty areas and dirty objects (i.e., regions or elements that contain edits that have not been reflected in the network connectivity index). The dirty areas and objects are identified and marked during editing of the network feature data. They are then subsequently cleaned as a byproduct of the incremental update of the connectivity network.