Theodoros Tzouramanis

Overlapping linear quadtrees: a spatio-temporal access method

Overlapping is a technique used in access methods to combiie consecutive structure instances into a single structure by not storing identical sub-stmctnres. This way, space is saved without sacrificing time performance. Here, we present the structure of Overlapping Linear Quadtrees -which is used to store consecutive rader images according to transaction tim~ Experimentation with synthetic region data shows that considerable storage is saved in comparison to independent linear quadtre~~, in the case of similar consecutive images. Therefore, this stmcture can be used in spati~ temporal databases to support. query processing of evolving images. Besides, an efficient aIgorithm that uses the new structure and answers spatio-temporal window queries is presented.

On the Generation of Time-Evolving Regional Data

Benchmarking of spatio-temporal databases is an issue of growing importance. In case large real data sets are not available, benchmarking requires the generation of artificial data sets following the real-world behavior of spatial objects that change their locations, shapes and sizes over time. Only a few innovative papers have recently addressed the topic of spatio-temporal data generators. However, all existing approaches do not consider several important aspects of continuously changing regional data. In this report, a new generator, called generator of time-evolving regional data (G-TERD), for this class of data is presented. The basic concepts that determine the function of G-TERD are the structure of complex 2-D regional objects, their color, maximum speed, zoom and rotation-angle per time slot, the influence of other moving or static objects on the speed and on the moving direction of an object, the position and movement of the scene-observer, the statistical distribution of each changing factor and finally, time. Apart from these concepts, the operation and basic algorithmic issues of G-TERD are presented. In the framework developed, the user can control the generator response by setting several parameters values. To demonstrate the use of G-TERD, the generation of a number of sample data sets is presented and commented. The source code and a visualization tool for using and testing the new generator are available on the Web.1 Thus, it is easy for the user to manipulate the generator according to specific application requirements and at the same time to examine the reliability of the underlying generalized data model.

Overlapping linear quadtrees and spatio-temporal query processing

In this paper, indexing in spatio-temporal databases by using the technique of overlapping is investigated. Overlapping has been previously applied in various access methods to combine consecutive structure instances into a single structure, without storing identical sub-structures. In this way, space is saved without sacrificing time performance. A new access method, overlapping linear quadtrees is introduced. This structure is able to store consecutive historical raster images, a database of evolving images. Moreover, it can be used to support query processing in such a database. Five such spatio-temporal queries along with the respective algorithms that take advantage of the properties of the new structure are introduced. The new access method was implemented and extensive experimental studies for space efficiency and query processing performance were conducted. A number of results of these experiments are presented. As far as space is concerned, these results indicate that, in the case of similar consecutive images, considerable storage is saved in comparison to independent linear quadtrees. In the case of query processing, the results indicate that the proposed algorithmic approaches outperform the respective straightforward algorithms, in most cases. The region data sets used in experiments were real images of meteorological satellite views and synthetic random images with specified aggregation.

Overlapping B + -trees: an implementation of a transaction time access method

Abstract A new variation of Overlapping B+-trees is presented, which provides efficient indexing of transaction time and keys in a two dimensional key-time space. Modification operations (i.e. insertions, deletions and updates) are allowed at the current version, whereas queries are allowed to any temporal version, i.e. either in the current or in past versions. Using this structure, snapshot and range-timeslice queries can be answered optimally. However, the fundamental objective of the proposed method is to deliver efficient performance in case of a general pure-key query (i.e. ‘history of a key’). The trade-off is a small increase in time cost for version operations and storage requirements.

Multiversion Linear Quadtree for Spatio-Temporal Data

Research in spatio-temporal databases has largely focused on extensions of access methods for the proper handling of time changing spatial information. In this paper, we present the Multiversion Linear Quadtree (MVLQ), a spatio-temporal access method based on Multiversion B-trees (MVBT) [2], embedding ideas from Linear Region Quadtrees [4]. More specifically, instead of storing independent numerical data having a different transaction-time each, for every consecutive image we store a group of codewords that share the same transaction-time, whereas each codeword represents a spatial subregion. Thus, the new structure may be used as an index mechanism for storing and accessing evolving raster images. We also conducted a thorough experimentation using sequences of real and synthetic raster images. In particular, we examined the time performance of temporal window queries, and provide results for a variety of parameter settings.

Benchmarking access methods for time-evolving regional data

In this paper we present a performance comparison of access methods for time-evolving regional data. Initially, we briefly review four temporal extensions of the Linear Region Quadtree: the Time-Split Linear Quadtree, the Multiversion Linear Quadtree, the Multiversion Access Structure for Evolving Raster Images and Overlapping Linear Quadtrees. These methods comprise a family of specialized access methods that can efficiently store and manipulate consecutive raster images. A new simpler implementation solution that provides efficient support for spatio-temporal queries referring to the past through these methods, is suggested. An extensive experimental space and time performance comparison of all the above access methods follows. The comparison is made under a common and flexible benchmarking environment in order to choose the best technique depending on the application and on the image characteristics. These experimental results show that in most cases the Overlapping Linear Quadtrees method is the best choice.

Processing of Spatio-Temporal Queries in Image Databases

Overlapping Linear Quadtrees is a structure suitable for storing consecutive raster images according to transaction time (a database of evolving images). This structure saves considerable space without sacrificing time performance in accessing every single image. Moreover, it can be used for answering efficiently window queries for a number of consecutive images (spatio-temporal queries). In this paper, we present three such temporal window queries: strict containment, border intersect and cover. Besides, based on a method of producing synthetic pairs of evolving images (random images with specified aggregation) we present empirical results on the I/O performance of these queries.

Chapter 6: Access Methods and Query Processing Techniques

The performance of a database management system (DBMS) is fundamentally dependent on the access methods and query processing techniques available to the system. Traditionally, relational DBMSs have relied on well-known access methods, such as the ubiquitous B + -tree, hashing with chaining, and, in some cases, linear hashing [52]. Object-oriented and object-relational systems have also adopted these structures to a great extend.

Time split linear quadtree for indexing image databases

The time split B-tree (TSBT) is modified for indexing a database of evolving binary images. This is accomplished by embedding ideas from linear region quadtrees that make the TSBT able to support spatio-temporal query processing. To improve query performance, additional pointers are added to the leaf-nodes of the TSBT. The resulting access method is called time split linear quadtree (TSLQ). Algorithms for processing five spatio-temporal queries have been adapted to the new structure. Such queries appear in multimedia systems, or geographical information systems (GIS), when searched by content. The TSLQ was implemented and results of extensive experiments on query time performance are presented, indicating that the proposed algorithmic approaches outbalance respective straightforward algorithms. The region data sets used in the experiments were real images of meteorological satellite views and synthetic raster images.

Secure Range Query Processing over Untrustworthy Cloud Services

Database-as-a-service is a relatively new cloud computing service offered on a pay-per-use basis and providing on-demand access to a database. The way data has dramatically increased in volume explains its success, while security and privacy issues arise, leaving enterprises, in particular, exposed to the risk of leakage of the data which they entrust to specialized cloud service providers or to other parties in order to reduce storage and query processing costs. Since traditional encryption does not support the execution of queries on encrypted data, this paper focuses on the problem of secure computation on encrypted data and puts forward a cloud database model that supports secure range query processing and retrieval of multi-dimensional (i.e. multi-attribute) data. It proposes two schemes to resist practical attacks operating on the basis of powerful background knowledge. A performance and efficiency evaluation of these schemes is also carried out to confirm their efficiency and practicability.