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...

: We present an efficient implementation method for temporal integrity constraints formulated in Past Temporal Logic. Although the constraints can refer to past states of the database, their checking does not require that the entire database history be stored. Instead, every database state is extended with auxiliary relations that contain the historical information necessary for checking constraints. Auxiliary relations can be implemented as materialized relational views. 1 Introduction Integrity constraints form an essential part of every database application. It is customary to distinguish between two kinds of constraints: static and temporal (or dynamic). Static constraints refer to the current state of the database, e.g.,"every manager is also an employee ", while temporal constraints may refer to past and future states in addition to the current state, e.g., "salaries of employees should never decrease" or "once a student drops out of the Ph.D. program, she should not be readmit...

Many papers have examined how to efficiently export a materialized view but to our knowledge none have studied how to efficiently import one. To import a view, i.e., to install a stream of updates, a real-time database system must process new updates in a timely fashion to keep the database "fresh," but at the same time must process transactions and ensure they meet their time constraints. In this paper, we discuss the various properties of updates and views (including staleness) that affect this tradeoff. We also examine, through simulation, four algorithms for scheduling transactions and installing updates in a soft real-time database. Keywords: soft real-time, temporal databases, materialized views, updates. 1 Introduction The problem we study in this paper arose during the ongoing implementation of the STRIP real-time database system. 1 This system [2] provides traditional database services (e.g., SQL, indexing, recovery) with real-time facilities (e.g., transaction deadlines,...

In environments where exact synchronization between source data objects and cached copies is not achievable due to bandwidth or other resource constraints, stale (out-of-date) copies are permitted. It is desirable to minimize the overall divergence between source objects and cached copies by selectively refreshing modified objects. We call the online process of selecting which objects to refresh in order to minimize divergence best-effort synchronization. In most approaches to best-effort synchronization, the cache coordinates the process and selects objects to refresh. In this paper, we propose a best-effort synchronization scheduling policy that exploits cooperation between data sources and the cache. We also propose an implementation of our policy that incurs low communication overhead even in environments with very large numbers of sources. Our algorithm is adaptive to wide fluctuations in available resources and data update rates. Through experimental simulation over synthetic and real-world data, we demonstrate the effectiveness of our algorithm, and we quantify the significant decrease in divergence achievable with source cooperation.

(DSMS) rely on time as a basis for windows on streams and for defining a consistent semantics for multiple streams and updatable relations. The system clock in a centralized DSMS provides a convenient and well-behaved notion of time, but often it is more appropriate for a DSMS application to define its own notion of time—its own clock(s), sequence numbers, or other forms of ordering and timestamping. Flexible application-defined time poses challenges to the DSMS, since streams may be out of order and uncoordinated with each other, they may incur latency reaching the DSMS, and they may pause or stop. We formalize these challenges and specify how to generate heartbeats so that queries can be evaluated correctly and continuously in an application-defined time domain. Our heartbeat generation algorithm is based on parameters capturing skew between streams, unordering within streams, and latency in streams reaching the DSMS. We also describe how to estimate these parameters at run-time, and we discuss how heartbeats can be used for processing continuous queries. 1.

In addition to satisfying data consistency requirements as in conventional database systems, concurrency control in real-time database systems must also satisfy timing constraints, such as deadlines associated with transactions. Concurrency control for a real time database system can be studied from several different perspectives. This largely depends on how the system is specified in terms of data consistency requirements and timing constraints. The objective of this research is to investigate and propose concurrency control algorithms for real time database systems, that not only satisfy consistency requirements but also meet transaction timing constraints as much as possible, minimizing the percentage and average lateness of deadline-missing transactions.

More and more databases are being used in situations where realtime constraints exist. A set of misconceptions have arisen regarding what a real-time database is and the appropriateness of using conventional databases in real-time applications. Nine misconceptions are identified and discussed. Various research challenges are enumerated and explained. In total, the paper articulates the special nature of real-time databases. 1 Introduction In 1988 a paper entitled Misconceptions of Real-Time Computing was published [11]. This paper articulated the key differences between general purpose computing and real-time computing. The impact of the paper was significant in that it spurred a lot of research that specifically focussed on real-time issues. We believe that there is now a significant body of scientific and technological results in real-time computing, in part, due to the careful definition of real-time computing and the articulation of the important differences between real-time comp...

Concurrency control for a real-time database must maintain both the traditional logical consistency constraints of data and transactions, and the additional temporal consistency constraints of data and transactions. Furthermore, the concurrency control should have the ability to express the trade-off that results from the inherent conflict between temporal and logical consistency constraints. The concurrency control should also be able to maintain and bound any imprecision that results from trading off logical consistency for temporal consistency.

This paper provides a systematic and comprehensive study of the underlying semantics of temporal databases, summarizing the results of an intensive collaboration between the two authors over the last five years. We first examine how facts may be associated with time, most prominently with one or more dimensions of valid time and transaction time. One common case is that of a bitemporal relation, in which facts are associated with exactly one valid time and one transaction time. These two times may be related in various ways, yielding temporal specialization. Multiple transaction times arise when a fact is stored in one database, then later replicated or transferred to another database. By retaining the transaction times, termed temporal generalization, the original relation can be effectively queried by referencing only the final relation. We attempt to capture the essence of time-varying information via a very simple data model, the bitemporal conceptual data model. Emphasis is placed...

The demand for real-time data services is increasing in many applications including e-commerce, agile manufacturing, and telecommunications network management. In these applications, it is desirable to execute transactions within their deadlines, i.e., before the real-world status changes, using fresh (temporally consistent) data. However, meeting these fundamental requirements is challenging due to dynamic workloads and data access patterns in these applications. Further, transaction timeliness and data freshness requirements may conflict. In this paper, we define average/transient deadline miss ratio and new data freshness metrics to let a database administrator specify the desired quality of real-time data services for a specific application. We also present a novel QoS management architecture for real-time databases to support the desired QoS even in the presence of unpredictable workloads and access patterns. To prevent overload and support the desired QoS, the presented architecture applies feedback control, admission control, and flexible freshness management schemes. A simulation study shows that our QoS-aware approach can achieve a near zero miss ratio and perfect freshness, meeting basic requirements for real-time transaction processing. In contrast, baseline approaches fail to support the desired miss ratio and/or freshness in the presence of unpredictable workloads and data access patterns.