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...

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...

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...

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

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.

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...

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.

We study competitive on-line scheduling in multi-processor real-time environments. In our model, every task has a deadline and a value that it obtains only if it completes by its deadline. A task can be assigned to any processor, all of which are equally powerful. The problem is to design an on-line scheduling algorithm (i.e., one in which the scheduler has no knowledge of a task until it is released) with worst case guarantees as to the total value obtained by the system. We study systems with two or more processors. We present an inherent limit on the best competitive guarantee that any on-line parallel real-time scheduler can give. Then we present a competitive algorithm that achieves a worst case guarantee which is within a small constant factor from the best possible guarantee in many cases. We consider two memory models: a distributed system having a centralized scheduler and a shared memory multiprocessor. 1 Introduction In modern life, real-time computer systems are gaining im...

In recent years, a demand for real-time systems that can manipulate large amounts of shared data has led to the emer-gence of real-time database systems (RTDBS) as a research area. This paper focuses on the problem of scheduling queries in RTDBSs. We introduce and evaluate a new algorithm called Priority Adaptation Query Resource Scheduling (PAQRS) for handling both single class and multiclass query workloads. The performance objective of the algorithm is to minimize the number of missed deadlines, while at the same time ensuring that any deadline misses are scattered across the different classes according to an administratively-defined miss distribution. This objective is achieved by dynamically adapting the system’s admission, mem-ory allocation, and priority assignment policies according to its current resource configuration and workload characteristics. A series of experiments confirms that PAQRS is very effective for real-time query scheduling.

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.