Analysis of concurrency control protocols for real-time database systems

Cataloged from PDF version of article.This paper provides an approximate analytic solution method for evaluating the performance of concurrency control protocols developed for real-time database systems (RTDBSs). Transactions processed in a RTDBS are associated with timing constraints typically in the form of deadlines. The primary consideration in developing a RTDBS concurrency control protocol is the fact that satisfaction of the timing constraints of transactions is as important as maintaining the consistency of the underlying database. The proposed solution method provides the evaluation of the performance of concurrency control protocols in terms of the satisfaction rate of timing constraints. As a case study, a RTDBS concurrency control protocol, called High Priority, is analyzed using the proposed method. The accuracy of the performance results obtained is ascertained via simulation. The solution method is also used to investigate the real-time performance benefits of the High Priority over the ordinary Two-Phase Locking. © 1998 Elsevier Science Inc. All rights reserved

Comparing two-phase locking and optimistic concurrency control protocols in multiprocessor real-time databases

Previous studies (Haritsa et al., 1990) have shown that optimistic concurrency control (OCC) generally performs better than lock-based protocols in disk-based real-time database systems (RTDBS). We compare the two concurrency control protocols in both disk-based and memory-resident multiprocessor RTDBS. Based on their performance characteristics, a new lock-based protocol, called two phase locking-lock write all (2PL-LW), is proposed. The results of our performance evaluation experiments show that different characteristics of the two environments indeed have great impact on the protocols' performance. We identify such system characteristics and show that our new lock-based protocols, 2PL-LW, is better than OCC in meeting transaction deadlines in both disk-based and memory-resident RTDBS.published_or_final_versio

The response-time distribution in a real-time database with optimistic concurrency control and general execution times

For a real-time shared-memory database with optimistic concurrency control, an approximation for the distribution of the transaction response time and thus for the deadline miss probability is obtained. Transactions arrive at the database according to a Poisson process. There is a limited number of CPUs that can handle transactions in parallel. Transactions have soft deadlines, and the probability of data conflicts is equal for all transactions. No restrictive assumptions are needed about the execution time of transactions: it can have any general probability distribution. We approximate the behavior of the system by a multi-server queue with a special type of feedback. The analysis of this queueing system is based on an interpolation of the corresponding systems with constant and exponential execution times. Numerical experiments, which compare the approximative analysis with a simulation of the database, show that the approximation of the response-time distribution is quite accurate and thus very useful for real-time database design

Incorporating real-time scheduling methods into database management systems

Many database applications today are characterised by the requirement of timely access to data. This requirement leads to an increasing trend towards adapting real-time scheduling techniques to the management of data access requests. In this paper, we summarise and stimulate developments of time-cognisant scheduling techniques for database management systems. In particular, we review briefly the methods used in mapping timing constraints of transactions into priorities, and the priority-based protocols used for concurrency control. We also suggest useful directions for future research

Speculative Concurrency Control for Real-Time Databases

In this paper, we propose a new class of Concurrency Control Algorithms that is especially suited for real-time database applications. Our approach relies on the use of (potentially) redundant computations to ensure that serializable schedules are found and executed as early as possible, thus, increasing the chances of a timely commitment of transactions with strict timing constraints. Due to its nature, we term our concurrency control algorithms Speculative. The aforementioned description encompasses many algorithms that we call collectively Speculative Concurrency Control (SCC) algorithms. SCC algorithms combine the advantages of both Pessimistic and Optimistic Concurrency Control (PCC and OCC) algorithms, while avoiding their disadvantages. On the one hand, SCC resembles PCC in that conflicts are detected as early as possible, thus making alternative schedules available in a timely fashion in case they are needed. On the other hand, SCC resembles OCC in that it allows conflicting transactions to proceed concurrently, thus avoiding unnecessary delays that may jeopardize their timely commitment

Concurrence control for transactions with priorities

Priority inversion occurs when a process is delayed by the actions of another process with less priority. With atomic transactions, the concurrency control mechanism can cause delays, and without taking priorities into account can be a source of priority inversion. Three traditional concurrency control algorithms are extended so that they are free from unbounded priority inversion

Tuning the Level of Concurrency in Software Transactional Memory: An Overview of Recent Analytical, Machine Learning and Mixed Approaches

Synchronization transparency offered by Software Transactional Memory (STM) must not come at the expense of run-time efficiency, thus demanding from the STM-designer the inclusion of mechanisms properly oriented to performance and other quality indexes. Particularly, one core issue to cope with in STM is related to exploiting parallelism while also avoiding thrashing phenomena due to excessive transaction rollbacks, caused by excessively high levels of contention on logical resources, namely concurrently accessed data portions. A means to address run-time efficiency consists in dynamically determining the best-suited level of concurrency (number of threads) to be employed for running the application (or specific application phases) on top of the STM layer. For too low levels of concurrency, parallelism can be hampered. Conversely, over-dimensioning the concurrency level may give rise to the aforementioned thrashing phenomena caused by excessive data contention—an aspect which has reflections also on the side of reduced energy-efficiency. In this chapter we overview a set of recent techniques aimed at building “application-specific” performance models that can be exploited to dynamically tune the level of concurrency to the best-suited value. Although they share some base concepts while modeling the system performance vs the degree of concurrency, these techniques rely on disparate methods, such as machine learning or analytic methods (or combinations of the two), and achieve different tradeoffs in terms of the relation between the precision of the performance model and the latency for model instantiation. Implications of the different tradeoffs in real-life scenarios are also discussed