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. This paper explores the issues in real-time database systems and presents an overview of the state of the art. After introducing the characteristics of data and transactions in real-time databases, we discuss issues that relate to the processing of time-constrained transactions. Specifically, we examine different approaches to resolving contention over data and processing resources. We also explore the problems of recovery, managing I/O, and handling overloads. Real-time databases have the potential...

Earlier studies have observed that in moderately-loaded real-time database systems, using an Earliest Deadline policy to schedule tasks results in the fewest missed deadlines. When the real-time system is overloaded, however, an Earliest Deadline schedule performs worse than most other policies. This is due to Earliest Deadline giving the highest priority to transactions that are close to missing their deadlines. In this paper, we present a new priority assignment algorithm called Adaptive Earliest Deadline (AED), which features a feedback control mechanism that detects overload conditions and modifies transaction priority assignments accordingly. Using a detailed simulation model, we compare the performance of AED with respect to Earliest Deadline and other fixed priority schemes. We also present and evaluate an extension of the AED algorithm called Hierarchical Earliest Deadline (HED), which is designed to handle applications that assign different values to transactions and where the...

In a recent study, we have shown that in real-time database systems that discard late transactions, optimistic concurrency control outperforms locking. Although the optimistic algorithm used in that study, OPT-BC, did not factor in transaction deadlines in making data conflict resolution decisions, it still outperformed a deadline-cognizant locking algorithm. In this paper, we discuss why adding deadline information to optimistic algorithms is a non-trivial problem, and describe some alternative methods of doing so. We present a new real-time optimistic concurrency control algorithm, WAlT-50, that monitors transaction conflict states and gives precedence to urgent transactions in a controlled manner. WAIT-50 is shown to provide significant performance gains over OPT-BC under a variety of operating conditions and workloads. 1.

Due to its potential for a high degree of parallelism, optimistic concurrency control is expected to perform better than two-phase locking when integrated with priority-driven CPU scheduling in real-time database sys-tems. In this paper, we examine the overall effects and the impact of the overheads in-volved in implementing real-time optimistic concurrency control. Using a locking mecha-nism to ensure the correctness of the imple-mentation, we develop a set of optimistic con-currency control protocols and evaluate them on a testbed. Throu h experiments, we in-vestigate, in depth, t R e effect of the locking mechanism on the performance of optimistic concurrency control protocols, and we com-pare the locking-based optimistic approach with a class of two-phase locking protocols. The experimental results indicate that the physical implementation schemes have a sig-nificant impact on the performance of real-time optimistic concurrency control. 1

In a distributed environment, tasks often have processing demands on multiple different sites. A distributed task is usually divided up into several subtasks, each one to be executed at some site in order. In a real-time system, an overall deadline is usually specified by an application designer indicating when a distributed task is to be finished. However, the problem of how a global deadline is automatically translated to the deadline of each individual subtask has not been well studied. This paper examines (through simulations) four strategies for subtask deadline assignment in a distributed soft real-time environment. Keywords: soft real-time, distributed systems, deadline assignment, scheduling. 1 Introduction Consider a radar surveillance system whose task is to track flying objects, decide whether an object is friendly or hostile, and in the latter case, come up with a combat strategy. This system requires the cooperation of several different components: a radar sensor componen...

A major challenge addressed by conventional database systems has been to efficiently implement the tran- - t saction model, which provides the properties of atomicity, serializability, and permanence. Real-time applications have added a complex new dimension to this challenge by placing deadlines on the response time of the o database system. In this paper, we examine the problem of real-time data access scheduling, that is, the problem f scheduling the data accesses of real-time transactions in order to meet their deadlines. In particular, we focus t on "firm deadline" real-time database applications, where transactions that miss their deadlines are discarded and he objective of the real-time database system is to minimize the number of missed deadlines. Within this - c framework, we use a detailed simulation model to compare the performance of several real-time locking proto ols and optimistic concurrency control algorithms under a variety of real-time transaction workloads. The , t results of our study show that in moving from the conventional database system domain to the real-time domain here are new performance-related forces that come into effect. Our experiments demonstrate that these factors a can cause performance recommendations that were valid in a conventional database setting to be significantly ltered in the corresponding real-time setting.

Many stream-based applications have sophisticated data processing requirements and real-time performance expectations that need to be met under asynchronous, time-varying data streams. In order to address these challenges, we propose novel operator scheduling approaches that specify (1) which operators to schedule (2) in which order to schedule the operators, and (3) how many tuples to process at each execution; and study them in the context of the Aurora data stream manager. We argue and provide experimental evidence that a fine-grained scheduling approach in combination with various scheduling techniques (such as batching of operators and tuples) can significantly improve the efficiency by reducing various system overheads. We also discuss application-aware extensions that address Quality of Service (QoS) issues by making scheduling decisions according to tuple processing delays and per-application QoS specifications. Finally, we present prototype-based experimental results that characterize the efficiency and effectiveness of our approaches under various stream workloads and processing scenarios. 1

this paper, after a quick introduction to O++ in Section 2, we state our design goals in providing trigger and constraint facilities for an object-oriented database in Section 3. We then describe the constraint and trigger facilities in Ode and illustrate their use in Sections 4 through 6. We also discuss issues related to constraints and triggers such as intra-object versus inter-object constraints and triggers, and referential integrity. In Section 7 we give details about the implementation of Ode triggers and constraints. Finally, in Section 8, we discuss constraint and trigger facilities in other systems.

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 isinvolved � and (2) certain aspects of concurrency control may not integrate well with real-time scheduling. In this paper, we rst 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 realtime 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 real-time database applications, we also discuss several approaches that explore the non-serializable semantics of real-time transactions to meet the hard deadlines. Index terms: concurrency control, real-time databases, real-time scheduling, real-time transactions, serializability, schedulability.

In this paper, issues involved in the design of a real-time database which maintains data temporal consistency are discussed. The concept of data-deadline is introduced and time cognizant non-waiting transaction scheduling policies are proposed. Informally, data-deadline can be viewed as the deadline that a transaction implicitly gets due to the temporal constraints of the data accessed by the transaction. Further, two time cognizant forced wait policies which improve performance significantly by forcing a transaction to delay further execution until a new version of sensor data becomes available are proposed. A way to exploit temporal data similarity to improve performance is also proposed. Finally, these policies are evaluated through detailed simulation experiments. The simulation results show that taking advantage of temporal data semantics in transaction scheduling can significantly improve the performance of user transactions in real-time database systems. In particular, it is d...