A Generic Framework for Monitoring Continuous Spatial Queries over Moving Objects.

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Presentation transcript:

A Generic Framework for Monitoring Continuous Spatial Queries over Moving Objects

Outline Introduction Related Work The Framework Overview Query Evaluation and Reevaluation Safe Region Computation Enhancements Performance Evaluation Conclusion

Introduction With the advent of mobile and ubiquitous computing, monitoring continuous spatial queries over moving objects has become a necessity for various daily applications, such as fleet management, cargo tracking, child care, and location-aware advertisement.

Introduction

Existing studies on continuous query monitoring focused on reducing the evaluation cost only. The previous studies were designed to support specific query types only.

Introduction

The first monitoring scheme that addresses the location update issue. The framework is generic in the sense that it is not designed for a specific query type. The framework offers accurate monitoring results at any time. Query reevaluation in this framework is triggered by location updates only.

Related Work Time-Parameterized R-Tree STRIPES Q-index SINA

The Framework Overview At the database server, all registered queries can be fit into main memory whereas not all the moving objects can. The database server handles location updates sequentially. The communication cost between every client and the database server is constant. Mobile clients are able to detect their locations

The Database Server

The Object Index The object index stores the current safe regions of all the objects. Since the safe region changes each time the object updates its location, the index should be optimized to handle frequent updates.

The Query Index For each query, the database server stores: –The parameters of the query –The current query results –The quarantine area of the query

Query Evaluation and Reevaluation

Evaluating New Range Query Start from the index root and recursively traverse down the index entries that overlap the query rectangle until reaching the leaf entries where the safe regions are stored.

Evaluating New kNN Query

Reevaluating Range and kNN Queries The incremental reevaluation of an affected range query is straightforward. For an order-sensitive kNN query, there are three cases in reevaluation: –1) p is not in the quarantine area, but p lst is; –2) p is in the quarantine area, but p lst is not; –3) both p and p lst are in the quarantine area.

Safe Region Computation The safe region of a moving object p designates how far p can reach without affecting the results of any registered query. The safe region for a query Q is the rectangular region in which p does not affect Q’s result.

Safe Region Computation The server needs to re-compute the safe region of an object p in three cases: –During the evaluation of a new query Q –After processing a source-initiated location update of object p –During the processing of a source-initiated location update

Safe Region Computation

Safe Region for Range Query If Q is a range query and p is in its quarantine area, the safe region is simply the quarantine area itself. Otherwise, there are four possible rectangles within the cell that can serve as the safe region, each of which has one of its sides coincide with a side of the cell.

Safe Region for kNN Query

Safe Region for a Batch of Range Queries

Enhancements The object always moves steadily towards its destination, in other words, it follows a rough direction for a significantly long period of time. Each object is limited by a maximum moving speed.

Maximum Speed for Query Evaluation

Steady Movement for Safe Region Computation

Performance Evaluation Safe-Region-Based query monitoring (SRB) framework. Optimal monitoring (OPT) Periodic monitoring (PRD)

Simulation Setup

Impact of Communication Delay

Scalability

Sensitivity of SRB

Performance of the Enhancements

Conclusion The framework distinguishes itself from existing work by being the first to address the location update issue and to provide a common interface for monitoring mixed types of queries.