Efficient update method for indexing locations of moving objects

Mobile Data Management, 2002. …, 2002

With the rapid advances of wireless communications and positioning techniques, tracking the positions of moving objects is becoming increasingly feasible and necessary. Traditional spatial index structures are not suitable for storing these positions because of numerous update operations. To reduce the number of update operations, many existing approaches use a linear function to describe the movements of objects. In many real applications, however, the movements of objects are too complicated to be represented as a simple linear function. In this case, such approaches based on a linear function cannot reduce update cost efficiently. In this paper, we propose a novel R-tree based indexing technique called LUR-tree. This technique updates the structure of the index only when an object moves out of the corresponding MBR (minimum bounding rectangle). If a new position of an object is in the MBR, it changes only the position of the object in the leaf node. It can update the position of the object quickly and reduce update cost greatly. Since it is based on the R-tree, the LUR-tree also uses the same algorithms to process various types of queries as the R-tree. We present the experimental results which show that our technique outperforms other techniques

Technical Indexing of spatial database is discussed in this paper. Several methods of indexing moving objects will be presented taking into account the faults and strengths of each one, the two main types of applications that manage moving objects will be discussed. "2-level index" is one of the recent variant indexing relied on R-tree, thereafter this variant will be presented and located between types of applications, its principle performance will be explained, the main defect which is redundancy of nodes after each update will be shown, and finally our contribution to optimize it will be presented.

Tenth International Conference on Management of Data (COMAD), 2000

We describe an indexing method for parametric rectangles that were recently proposed in [6] to represent moving objects. Parametric rectangles are a more natural representation of moving objects than moving points. Our indexing method extends R-trees, with the following important modifications among others: (i) definition of parametric rectangle trees, or PR-trees (ii) searching a PR-tree for intersection queries (iii) insertion into PR-trees (iv) deletion from PRtrees. These modified operations need new algorithms for finding a minimum bounding parametric rectangle (MBPR) of a set of parametric rectangles and a new insertion and splitting criteria and algorithms. Experiments show that PR-trees provide a significant improvement over R-trees for intersection queries with moving rectangles.

Eighth International Conference on Database Systems for Advanced Applications, 2003. (DASFAA 2003). Proceedings., 2003

Moving object environments contain large numbers of queries and continuously moving objects. Traditional spatial index structures do not work well in this environment because of the need to frequently update the index which results in very poor performance. In this paper, we present a novel indexing structure, namely the Q+Rtree, based on the observation that i) most moving objects are in quasi-static state most of time, and ii) the moving patterns of objects are strongly related to the topography of the space. The Q+Rtree is a hybrid tree structure which consists of both an R-tree and a QuadTree. The Rtree component indexes quasi-static objects-those that are currently moving slowly and are often crowded together in buildings or houses. The Quadtree component indexes fast moving objects which are dispersed over wider regions. We also present the experimental evaluation of our approach.

2022

A TPR-tree is a well-known indexing structure that is developed to answer queries about the current or future time locations of moving objects. For the purpose of space efficiency, the TPR-tree employs the notion of VBR (velocity bounding rectangle) so that a regional rectangle presents varying positions of a group of moving objects. Since the rectangle computed from a VBR always encloses the possible maximum range of an indexed object group, a search process only has to follow VBR-based rectangles overlapped with a given query range, while searching toward candidate leaf nodes. Although the TPR-tree index shows up its space efficiency, it easily suffers from the problem of dead space that results from fast and constant expansions of VBR-based rectangles. Against this, the TPR-tree index is enforced to update leaf nodes for reducing dead spaces within them. Such an update-prone feature of the TPR-tree becomes more problematic when the tree is saved in flash storage. This is because ...

2013

Indexing moving objects usually involves a great amount of updates, caused by objects reporting their current position. In order to keep the present and past positions of the objects in secondary memory, each update introduces an I/O and this process is sometimes creating a bottleneck. In this paper we deal with the problem of minimizing the number of I/Os in such a way that queries concerning the present and past positions of the objects can be answered efficiently. In particular we propose two new approaches that achieve an asymptotically optimal number of I/Os for performing the necessary updates. The approaches are based on the assumption that the primary memory suffices for storing the current positions of the objects.

Computer Science and Information Systems, 2013

Indexing moving objects usually involves a great amount of updates, caused by objects reporting their current position. In order to keep the present and past positions of the objects in secondary memory, each update introduces an I/O and this process is sometimes creating a bottleneck. In this paper we deal with the problem of minimizing the number of I/Os in such a way that queries concerning the present and past positions of the objects can be answered efficiently. In particular we propose two new approaches that achieve an asymptotically optimal number of I/Os for performing the necessary updates. The approaches are based on the assumption that the primary memory suffices for storing the current positions of the objects.

Proceedings 18th International Conference on Data Engineering, 2002

Visionaries predict that the Internet will soon extend to billions of wireless devices, or objects, a substantial fraction of which will offer their changing positions to locationbased services. This paper assumes an Internet-service scenario where objects that have not reported their position within a specified duration of time are expected to no longer be interested in, or of interest to, the service. Due to the possibility of many "expiring" objects, a highly dynamic database results. The paper presents an R-tree based technique for the indexing of the current positions of such objects. Different types of bounding regions are studied, and new algorithms are provided for maintaining the tree structure. Performance experiments indicate that, when compared to the approach where the objects are not assumed to expire, the new indexing technique can improve search performance by a factor of two or more without sacrificing update performance.

Sigmod Record, 2000

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Journal of Computer Science and Technology, 2009

The task of selecting the most appropriate method for indexing the data according to application requires a careful comparison study of indices of interests. In particular, we consider object movements by tracing their trajectories within a predefined road network. MV3DR-tree and 3DR-tree constitute our first group indexing the objects moving in free movement scenarios. Besides, Mapping and MON-tree are the second group indexing the locations of objects moving over a network of road. Those access methods mainly organize a group of R-tree in order to index the underlying road network and the object movements. Our goal in this study is to evaluate existing proposals under fair circumstances with respect to storage consumption and spatio-temporal query execution performance. In our comparisons, we discuss the structure's sensibility to query's spatial and/or temporal extent as well as the tradeoff arising between two groups in terms of reliability and disk access performance. We believe that revealing the vulnerabilities of the selected structures, especially Mapping and MON-tree motivates us to design more robust organizations.