In this paper we propose a data model for representing moving objects in database systems. It is called the Moving Objects Spatio-Temporal (MOST) data model. We also propose Future Temporal Logic (FTL) as the query language for the MOST model, and devise an algorithm for processing FTL queries in MOST. 1. Introduction Existing database management systems (DBMS's) are not well equipped to handle continuously changing data, such as the position of moving objects. The reason for this is that in databases, data is assumed to be constant unless it is explicitly modified. For example, if the salary field is 30K, then this salary is assumed to hold (i.e. 30K is returned in response to queries) until explicitly updated. Thus, in order to represent moving objects (e.g. cars) in a database, and answer queries about their position (e.g., How far is the car with license plate RWW860 from the nearest hospital?) the car's position has to be continuously updated. This is unsatisfactory since either ...

Consider a database that represents information about moving objects and their location. For example, for a database representing the location of taxi-cabs a typical query may be: retrieve the free cabs that are currently within 1 mile of 33 N. Michigan Ave., Chicago (to pick-up a customer). In the military, moving objects database applications arise in the context of the digital battlefield, and in the civilian industry they arise in transportation systems. Currently, moving objects database applications are being developed in an ad hoc fashion. Database Management System (DBMS) technology provides a potential foundation upon which to develop these applications, however, DBMS's are currently not used for this purpose. The reason is that there is a critical set of capabilities that are needed by moving objects database applications and are lacking in existing DBMS's. The objective of our Databases fOr MovINg Objects (DOMINO) project is to build an envelope containing these capabilities...

A temporal database contains time-varying data. In a real-time database transactions have deadlines or timing constraints. In this paper we review the substantial research in these two heretofore separate research areas. We first characterize the time domain, then investigate temporal and real-time data models. We evaluate temporal and real-time query languages along several dimensions. Temporal and real-time DBMS implementation is examined. We conclude with a summary of the major accomplishments of the research to date, and list several research questions that should be addressed next. Keywords: object-oriented database, relational databases, query language, temporal data model, time-constrained database, transaction time, user-defined time, valid time 1 Introduction Time is an important aspect of all real-world phenomena. Events occur at specific points in time; objects and the relationships among objects exist over time. The ability to model this temporal dimension of the real worl...

Spatio-temporal databases deal with geometries changing over time. In general, geometries cannot only change in discrete steps, but continuously, and we are talking about moving objects. If only the position in space of an object is relevant, then moving point is a basic abstraction; if also the extent is of interest, then the moving region abstraction captures moving as well as growing or shrinking regions. We propose a new line of research where moving points and moving regions are viewed as three-dimensional (2D space + time) or higher-dimensional entities whose structure and behavior is captured by modeling them as abstract data types. Such types can be integrated as base (attribute) data types into relational, object-oriented, or other DBMS data models; they can be implemented as data blades, cartridges, etc. for extensible DBMSs. We expect these spatio-temporal data types to play a similarly fundamental role for spatio-temporal databases as spatial data types have played for sp...

This paper discusses the design and implementation of SEQ, a database system with support for sequence data. SEQ models a sequence as an ordered collection of records, and supports a declarative sequence query language based on an algebra of query operators, thereby permitting algebraic query optimization and evaluation. SEQ has been built as a component of the PREDATOR database system that provides support for relational and other kinds of complex data as well. There are three distinct contributions made in this paper. (1) We describe the specification of sequence queries using the SEQUIN query language. (2) We quantitatively demonstrate the importance of various storage and optimization techniques by studying their effect on performance. (3) We present a novel nested design paradigm used in PREDATOR to combine sequence ‘and relational data.

Abstract—An efficient multiversion access structure for a transaction-time database is presented. Our method requires optimal storage and query times for several important queries and logarithmic update times. Three version operations}inserts, updates, and deletes}are allowed on the current database, while queries are allowed on any version, present or past. The following query operations are performed in optimal query time: key range search, key history search, and time range view. The key-range query retrieves all records having keys in a specified key range at a specified time; the key history query retrieves all records with a given key in a specified time range; and the time range view query retrieves all records that were current during a specified time interval. Special cases of these queries include the key search query, which retrieves a particular version of a record, and the snapshot query which reconstructs the database at some past time. To the best of our knowledge no previous multiversion access structure simultaneously supports all these query and version operations within these time and space bounds. The bounds on query operations are worst case per operation, while those for storage space and version operations are (worst-case) amortized over a sequence of version operations. Simulation results show that good storage utilization and query performance is obtained. Index Terms—Transaction-time database, multidimensional data, access methods, data structures, indexing, I/O complexity.

This paper presents the model which is the basis for a system to manage various kinds of sequence data. The model separates the data from the ordering information, and includes operators based on two distinct abstractions of a sequence. The main contributions of the model are: (a) it can deal with different types of sequence data, (b) it supports an expressive range of sequence queries, (c) it draws from many of the diverse existing approaches to modeling sequence data. 1

Many applications require the ability to manipulate sequences of data. We motivate the importance of sequence query processing, and present a framework for the optimization of sequence queries based on several novel techniques. These include query transformations, optimizations that utilize meta--data, and caching of intermediate results. We present a bottom-up algorithm that generates an efficient query evaluation plan based on cost estimates. This work also identifies a number of directions in which future research can be directed. 1 Introduction Many real life applications manipulate data that is inherently sequential. Such data is logically viewed and queried in terms of a sequence abstraction and is often physically stored as a sequence. Databases should (a) allow sequences to be queried in a declarative manner, utilizing the ordered semantics of the data, and (b) take advantage of the opportunities available for query optimization. Relational databases are inadequate in this re...

In this paper we propose two languages, called Future Temporal Logic (FTL) and Past Temporal Logic (PTL), for specifying temporal triggers. Some examples of trigger conditions that can be specified in our language are the following: "The value of a certain attribute increases by more than 10% in ten minutes", "A tuple that satisfies a certain predicate is added to the database at least 10 minutes before another tuple, satisfying a different condition, is added to the database". Such triggers are important for monitor and control applications. In addition to the languages, we present algorithms for processing the trigger conditions specified in these languages, namely, procedures for determining when the trigger conditions are satisfied. These methods can be added as a "temporal" component to an existing database management systems. A preliminary prototype of the temporal component that uses the FTL language has been built on top of Sybase running on SUN workstations. Index Terms: Acti...

In this paper we propose a data model for representing moving objects with uncertain positions in database systems. It is called the Moving Objects Spatio-Temporal (MOST) data model. We also propose Future Temporal Logic (FTL) as the query language for the MOST model, and devise an algorithm for processing FTL queries in MOST. 1 Introduction Existing database management systems (DBMS's) are not well equipped to handle continuously changing data, such as the position of moving objects. The reason for this is that in databases, data is assumed to be constant unless it is explicitly modified. For example, if the salary field is 30K, then this salary is assumed to hold (i.e. 30K is returned in response to queries) until explicitly updated. Thus, in order to represent moving objects (e.g. cars) in a database, and answer queries about their position (e.g., How far is the car with license plate RWW860 from the nearest hospital?) the car's position has to be continuously updated. This is unsa...