Performance Of Concurrency Control Algorithms Research Articles

Key factors for improving performance of concurrency control algorithms

Abstract Five key factors for improving the performance of access methods with concurrency control features are presented. Three of these factors reflect search and concurrency control methods, and the other two explore the interference behaviors among a set of concurrent operations. These factors can be used as keys to improve the efficiency and robustness of a concurrency control algorithm (CCA) and as basic interpretations to explain why the performance of one CCA would be better (or worse) than another in a multi-user environment. To illustrate the applicability of these factors, two CCAs for R-trees were used as examples to explain how to improve the performance of a CCA using these five key factors.

Concurrency control in multidatabase systems: A performance study

Abstract A multidatabase system (MDBS) is a federation of multiple autonomous local database systems (LDBSs). Over the years, it has been recognized that the most challenging issue of concurrency control in an MDBS has been a concern about how to resolve indirect conflicts and thereby to ensure global serializability (GSR), without sacrificing the local autonomy. Even though the global serializability issue is well understood and many concurrency control algorithms have been proposed, it is noticeable that the performance trade-offs of those algorithms are not yet understood. To address issues about the performance of concurrency control algorithms in an MDBS, we examine two MDBS concurrency control algorithms through simulation: optimistic ticket method (OTM) and global ticket method (GTM) that we have proposed. In OTM, the GSR is assured by way of accessing a local object (ticket), by which any indirect conflicts that may cause non-serializable execution are resolved. The global transaction manager (Global_TM) in GTM maintains a global variable (ticket), which is similar to timestamp, and the commit order of a GT is predefined by the order of assigned global ticket value. We examine the performance trade-offs of the two concurrency control methods (CCMs) with respect to ensuring GSR in particular. To ensure GSR, the (GTs) are expected to frequently restart in OTM and block in GTM. In this study, we also investigate the implications of time-out interval on the performance as we assume that the time-out approach is used as a global deadlock resolution method for both algorithms. Our experimental results showed that GTM outperforms OTM in cases that short time-out values are given. However, in case that the time-out value relatively becomes long, our results demonstrated that OTM outperforms GTM.

Analysis of locking behavior in three real database systems

Concurrency control is essential to the correct functioning of a database due to the need for correct, reproducible results. For this reason, and because concurrency control is a well-formulated problem, there has developed an enormous body of literature studying the performance of concurrency control algorithms. Most of this literature uses either analytic modeling or random number-driven simulation, and explicitly or implicitly makes certain assumptions about the behavior of transactions and the patterns by which they set and unset locks. Because of the difficulty of collecting suitable measurements, there have been only a few studies which use trace-driven simulation, and still less study directed toward the characterization of concurrency control behavior of real workloads. In this paper, we present a study of three database workloads, all taken from IBM DB2 relational database systems running commercial applications in a production environment. This study considers topics such as frequency of locking and unlocking, deadlock and blocking, duration of locks, types of locks, correlations between applications of lock types, two-phase versus non-two-phase locking, when locks are held and released, etc. In each case, we evaluate the behavior of the workload relative to the assumptions commonly made in the research literature and discuss the extent to which those assumptions may or may not lead to erroneous conclusions.

Maintaining temporal consistency: pessimistic vs. optimistic concurrency control

We study the performance of concurrency control algorithms in maintaining temporal consistency of shared data in hard real time systems. In our model, a hard real time system consists of periodic tasks which are either write only, read only or update transactions. Transactions may share data. Data objects are temporally inconsistent when their ages and dispersions are greater than the absolute and relative thresholds allowed by the application. Real time transactions must read temporally consistent data in order to deliver correct results. Based on this model, we have evaluated the performance of two well known classes of concurrency control algorithms that handle multiversion data: the two phase locking and the optimistic algorithms, as well as the rate monotonic and earliest deadline first scheduling algorithms. The effects of using the priority inheritance and stack based protocols with lock based concurrency control are also studied. >

Probabilistic analysis of transaction blocking under arbitrary data access distribution in database systems

Past analytic studies of concurrency control algorithms for database systems have assumed that data access distributions of transactions are uniformly distributed across the entire database. This assumption is largely forced by the fact that computation of the probability of transaction blocking due to conflicts in case of an arbitrary access distribution is impractical (due to combinatorial explosion), even for a database of small size. However, this assumption is unrealistic because in real-life databases, transactions exhibit locality of data reference [16, 21, 25]. Since the probability of conflicts among transactions is sensitive to the data access distribution of transactions, and since the performance of concurrency control algorithms is sensitive to the probability of conflicts, it is important that performance studies of concurrency control algorithms be carried out for arbitrary data access distribution. To assist the performance analysis of concurrency control algorithms under arbitrary data access distributions, in this paper we present an analysis of transaction blocking under arbitrary data access distribution. We present a polynomial time algorithm for computation of probability of conflicts among a set of transactions of given size for databases where data access distribution is arbitrary. Direct computation of this probability from the expression has exponential complexity, and complexity of computation of this probability under uniform data access case is constant. We illustrate the proposed technique by taking a numerical example, and show that the assumption of uniform data access distribution can introduce significant error.

Hierarchical timestamping algorithm

The Hierarchical Timestamping Algorithm is proposed for handling database concurrency control. By analyzing transaction conflicts and partitioning the data base into hierarchical partitions to which transactions will access discriminantly using different synchronization protocols, the algorithm can offer significant performance gain. It also reduces the need for transactions to leave traces (e.g. locks, timestamps) when accessing a data element. It is shown that the algorithm is correct in terms of transaction serializability. This is done by showing that the algorithm enforces a topological order among transactions. This research advocates the potential benefit of application analysis in enhancing performance of concurrency control algorithms where the level of concurrency is vital to system performance.

Concurrency control performance modeling: alternatives and implications

A number of recent studies have examined the performance of concurrency control algorithms for database management systems. The results reported to date, rather than being definitive, have tended to be contradictory. In this paper, rather than presenting “yet another algorithm performance study,” we critically investigate the assumptions made in the models used in past studies and their implications. We employ a fairly complete model of a database environment for studying the relative performance of three different approaches to the concurrency control problem under a variety of modeling assumptions. The three approaches studied represent different extremes in how transaction conflicts are dealt with, and the assumptions addressed pertain to the nature of the database system's resources, how transaction restarts are modeled, and the amount of information available to the concurrency control algorithm about transactions' reference strings. We show that differences in the underlying assumptions explain the seemingly contradictory performance results. We also address the question of how realistic the various assumptions are for actual database systems.

Performance analysis of an algorithm for concurrency control in replicated database systems

In this paper, we analyze the performance of a concurrency control algorithm for replicated database systems. We present a model of a distributed database system which provides a framework to study the performance of different concurrency control algorithms. We discuss performance criteria to evaluate different algorithms. We use the model to analyze the performance of an algorithm for concurrency control in replicated database systems. The technique used in analysis is iterative and approximate. We plot a set of performance measures for several values of the model parameters. The results of analysis are compared against a simulation study.