The Weighted Shortest Path Search in Mobile GIS Services.
ABSTRACT Traditional GIS buffer inquiries focus on the length of the road path on map only. In this paper, an expanded method is proposed
to support the distribution of mobile GIS services. According to the user’s requirement and known buffer area radius on map,
we defined the factors to calculate the optimal path from one node to the target node in a map, which considers not only the
length of the road, but also traffic flow, road cost and other factors. We use the integrated cost to re-define the road path
weights, and then select the optimal path among the road based on the minimum weight. The actual experimental results shown
that based on the quantified traffic flow and road condition, from node to other target nodes, we can get an optimal path
on map, which satisfies the condition mostly. The results can greatly assist the inquiry of the optimal path in GIS services.
Conference Proceeding: Adaptive nearest neighbor queries in travel time networks.[show abstract] [hide abstract]
ABSTRACT: Nearest neighbor (NN) searches represent an important class of queries in geographic information systems (GIS). Most nearest neighbor algorithms rely on static distance information to compute NN queries (e.g., Euclidean distance or spatial network distance). However, the final goal of a user when performing an NN search is often to travel to one of the points of the search result. In this case, finding the nearest neighbors in terms of travel time is more important than the actual distance. In the existing NN algorithms dynamic real-time events (e.g., traffic congestions, detours, etc.) are usually not considered and hence the pre-computed nearest neighbor objects may not accurately reflect the shortest travel time. In this paper we propose a novel travel time network that integrates both spatial networks and real-time traffic event information. Based on this foundation of the travel time network, we develop a local-based greedy nearest neighbor algorithm and a global-based adaptive nearest neighbor algorithm that both utilize real-time traffic information to provide adaptive nearest neighbor search results. We have performed a theoretical analysis and simulations to verify our methods. The results indicate that our algorithms remarkably reduce the travel time compared with previous nearest neighbor solutions.13th ACM International Workshop on Geographic Information Systems, ACM-GIS 2005, November 4-5, 2005, Bremen, Germany, Proceedings; 01/2005
Conference Proceeding: Query Processing in Spatial Network Databases.[show abstract] [hide abstract]
ABSTRACT: Despite the importance of spatial networks in real-life applications, most of the spatial database literature focuses on Euclidean spaces. In this paper we propose an architecture that integrates network and Euclidean information, capturing pragmatic constraints. Based on this architecture, we develop a Euclidean restriction and a network expansion framework that take advantage of location and connectivity to efficiently prune the search space. These frameworks are successfully applied to the most popular spatial queries, namely nearest neighbors, range search, closest pairs and e- distance joins, in the context of spatial network databases.01/2003
- INFOCOM 2006. 25th IEEE International Conference on Computer Communications, Joint Conference of the IEEE Computer and Communications Societies, 23-29 April 2006, Barcelona, Catalunya, Spain; 01/2006