Data in real-time databases has to be logically consistent as well as temporally consistent. The latter arises from the need to preserve the temporal validity of data items that reflect the state of the environment that is being controlled by the system. Some of the timing constraints on the transactions that process real-time data come from this need. These constraints, in turn, necessitate time-cognizant transaction processing so that transactions can be processed to meet their deadlines.

Real-time databases

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 previously separate areas. First we characterize the time domain; then we investigate temporal and real-time data models. We evaluate temporal and real-time query languages along several dimensions. We examine temporal and real-time DBMS implementation. Finally, we summarize major research accomplishments to date and list several unanswered research questions. >

Temporal and real-time databases: a survey

In addition to maintaining database consistency as in conventional databases, real-time database systems must also handle transactions with timing constraints. While transaction response time and throughput are usually used to measure a conventional database system, the percentage of transactions satisfying the deadlines or a time-critical value function is often used to evaluate a real-time database system. Scheduling real-time transactions is far more complex than traditional real-time scheduling in the sense that (1) worst case execution times are typically hard to estimate, since not only CPU but also I/O requirement is involved; and (2) certain aspects of concurrency control may not integrate well with real-time scheduling. In this paper, we first develop a taxonomy of the underlying design space of concurrency control including the various techniques for achieving serializability and improving performance. This taxonomy provides us with a foundation for addressing the real-time issues. We then consider the integration of concurrency control with real-time requirements. The implications of using run policies to better utilize real-time scheduling in a database environment are examined. Finally, as timing constraints may be more important than data consistency in certain hard realtime database applications, we also discuss several approaches that explore the nonserializable semantics of real-time transactions to meet the hard deadlines. >

On real-time databases: concurrency control and scheduling

Typically, a real–time system consists of a a controlling system and a controlled system. In an automated factory, the controlled system is the factory floor with its robots, assembling stations, and the assembled parts, while the controlling system is the computer and human interfaces that manage and coordinate the activities on the factory floor. Thus, the controlled system can be viewed as the environment with which the computer interacts. The controlling system interacts with its environment based on the data available about the environment, say from various sensors, e.g. temperature and pressure sensors. It is imperative that the state of the environment, as perceived by the controlling system, be consistent with the actual state of the environment. Otherwise, the effects of the controlling systems’ activities may be disastrous. Hence, timely monitoring of the environment as well as timely processing of the sensed information is necessary. The sensed data is processed further to derive new data. For example, the temperature and pressure information pertaining to a reaction may be used to derive the rate at which the reaction appears to be progressing. This derivation typically would depend on past temperature and pressure trends and so some of the needed information may have to be fetched from archival storage. Based on the derived data, where the derivation may involve multiple steps, actuator commands are set. For instance, in our example, the derived reaction rate is used to determine the amount of chemicals or coolant to be added to the reaction. In general, the history of (interactions with) the environment are also logged in archival storage. In addition to the timing constraints that arise from the need to continuously track the environment, timing correctness requirements in a real–time (database) system also arise because of the need to make data available to the controlling system for its decision-making activities. If the computer controlling a robot does not command it to stop or turn on time, the robot might collide with another object on the factory floor. Needless to say, such a mishap can result in a major catastrophe. Besides robotics, applications such as medical patient monitoring, programmed stock trading, and military command and control systems like submarine contact tracking require timely actions as well as the ability to access and store complex data that reflects the state of the application’s environment. That is, data in these applications must be valid, or fresh, when it is accessed in order for the application to perform correctly. In a patient monitoring system, data such as heart rate, temperature, and blood pressure must be collected periodically. Transactions that monitor the danger level of a patient’s status must be performed within a specified time, and the data must be accessed within an interval that defines the validity of the data. If not, the computations made by the transactions do not reflect the current state of the patient’s health. A traditional database provides some of the functionality required by these applications, such as coordination of concurrent actions and consistent access to shared data. But they do not provide for enforcement of the

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Real-Time Databases and Data Services

A database system supporting a real-time application has to provide real-time information to the executing transactions. Each real-time transaction is associated with a timing constraint, typically in the form of a deadline. It is difficult to satisfy all timing constraints due to the consistency requirements of the underlying database. In scheduling the transactions it is aimed to process as many transactions as possible within their deadlines. Replicated database systems possess desirable features for real-time applications, such as a high level of data availability, and potentially improved response time for queries. On the other hand, multiple copy updates lead to a considerable overhead due to the communication required among the data sites holding the copies. In this paper, we investigate the impact of storing multiple copies of data on satisfying the timing constraints of real-time transactions. A detailed performance model of a distributed database system is employed in evaluating the effects of various workload parameters and design alternatives on the system performance. The performance is expressed in terms of the fraction of satisfied transaction deadlines. A comparison of several real-time concurrency control protocols, which are based on different approaches in involving timing constraints of transactions in scheduling, is also provided in performance experiments.

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Processing real-time transactions in a replicated database system

Real-time multiversion concurrency control algorithms are proposed, to: increase concurrency, adjust the serialization order dynamically and work without an estimate of a transaction's runtime. The authors also propose disk scheduling algorithms which consider not only the transactions which request input/output (I/O) but also those affected by I/O. They consider transactions which are directly affected when priorities of I/O requests are assigned, in addition to transactions which generates these requests. The real-time disk resident database system model and the multiversion concurrency control algorithms are described. The real-time disk scheduling algorithms and their properties are also described. Real-time multiversion concurrency control and disk scheduling algorithms are shown to decrease miss ratio significantly. >

W. Kim

Papers

Enhancing real-time DBMS performance with multiversion data and priority based disk scheduling