716366
Distributed Continuous Range Query Processing on Moving Objects
Recent work on continuous queries has focused on processing queries in very large, mobile environments. In this paper, we propose a system leveraging the computing capacities of mobile devices for continuous range query processing. In our design, continuous range queries are mainly processed on the mobile device side, which is able to achieve real-time updates with minimum server load. Our work distinguish itself from previous work with several important contributions. First, we introduce a distributed server infrastructure to partition the entire service region into a set of service zones and cooperatively handle requests of continuous range queries. This feature improves the robustness and flexibility of the system by adapting to a time-varying set of servers. Second, we propose a novel query indexing structure, which records the difference of the query distribution on a grid model. This approach significantly reduce the size and complexity of the index so that in-memory indexing can be achieved on mobile objects with constrained memory size. We report on the rigorous evaluation of our design, which shows substantial improvement in the efficiency of continuous range query processing in mobile environments.
10770318
ANNATTO: Adaptive Nearest Neighbor Queries in Travel Time Networks
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 search results. Based on this observation, finding the nearest neighbors in terms of travel time is more realistic 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 demonstration we present ANNATTO, a novel adaptive nearest neighbor query model for travel time networks which integrates both spatial networks and real-time traffic event information. The ANNATTO system includes the implementation of a globalbased adaptive nearest neighbor algorithm and a localbased greedy nearest neighbor algorithm that both utilize real-time traffic information to provide adaptive nearest neighbor search results.
37559091
Web Services Enabled E-Market Access Control (EMAC)
5230665
Finding global icebergs over distributed data sets
Finding icebergs–items whose frequency of occurrence is above a certain threshold–is an important problem with a wide range of applications. Most of the existing work focuses on iceberg queries at a single node. However, in many real-life applications, data sets are distributed across a large number of nodes. Two naïve approaches might be considered. In the first, each node ships its entire data set to a central server, and the central server uses single-node algorithms to find icebergs. But it may incur prohibitive communication overhead. In the second, each node submits local icebergs, and the central server combines local icebergs to find global icebergs. But it may fail because in many important applications, globally frequent items may not be frequent at any node. In this work, we propose two novel schemes that provide accurate and efficient solutions to this problem: a sampling-based scheme and a counting-sketch-based scheme. In particular, the latter scheme incurs a communication cost at least an order of magnitude smaller than the naïve scheme of shipping all data, yet is able to achieve very high accuracy. Through rigorous theoretical and experimental analysis we establish the statistical properties of our proposed algorithms, including their accuracy bounds.
783838
Practical Indexing XML Document for Twig Query
Answering structural queries of XML with index is an important approach of efficient XML query processing. Among existing structural indexes for XML data, F&B index is the smallest index that can answer all branching queries. However, an F&B index for less regular XML data often contains a large number of index nodes, and hence a large amount of main memory. If the F&B index cannot be accommodated in the available memory, its performance will degrade significantly. This issue has practically limited wider application of the F&B index. 
 
In this paper, we propose a disk organization method for the F&B index which shift part of the leave nodes in the F&B index to the disk and organize them judiciously on the disk. Our method is based on the observation that the majority of the nodes in a F&B index is often the leaf nodes, yet their access frequencies are not high. 
 
We select some leaves to output to disk. With the support of reasonable storage structure in main memory and in disk, we design efficient query processing method). We further optimize the design of the F&B index based on the query workload. Experimental results verified the effectiveness of our proposed approach.
9370677
Towards space: time light field rendering
So far extending light field rendering to dynamic scenes has been trivially treated as the rendering of static light fields stacked in time. This type of approaches requires input video sequences in strict synchronization and allows only discrete exploration in the temporal domain determined by the capture rate. In this paper we propose a novel framework, space-time light field rendering, which allows continuous exploration of a dynamic scene in both spatial and temporal domain with unsynchronized input video sequences.In order to synthesize novel views from any viewpoint at any time instant, we develop a two-stage rendering algorithm. We first interpolate in the temporal domain to generate globally synchronized images using a robust spatial-temporal image registration algorithm followed by edge-preserving image morphing. We then interpolate those software-synchronized images in the spatial domain to synthesize the final view. Our experimental results show that our approach is robust and capable of maintaining photo-realistic results.
5809000
VIBRANT: A Brainstorming Agent for Computer Supported Creative Problem Solving
This paper describes key issues underlying the design of a tutoring system that brainstorms with students in order to support qualitative problem solving. Cognitively oriented and socially oriented support are enabled by two technologies, namely heuristic-based feedback generation and community-data-driven social recommendation. Formal representations and corresponding automated reasoning procedures for these technologies are introduced.