Can-Follow Concurrency Control
ABSTRACT Can-follow concurrency control permits a transaction to read (write) an item write-locked (read-locked) by another transaction with almost no delays. By combining the merits of 2PL and 2V2PL, this approach mitigates the lock contention not only between update and read-only transactions, but also between update and update transactions.
- SourceAvailable from: dtic.mil[Show abstract] [Hide abstract]
ABSTRACT: The primary accomplishment of this project is a new paradigm for secure database system design, intrusion tolerant database systems. In particular, an innovative intrusion tolerant database system framework, denoted ITDB, is developed. While traditional secure database systems rely on preventive controls, ITDB can detect intrusions, isolate attacks, contain, assess and repair the damage caused by intrusions in a timely manner such that a self-stabilized level of data integrity and availability can be provided to applications. Built on top of COTS DBMS, ITDB arms commercial database servers with the ability to deliver sustained valid data access services even in the face of intensive attacks. To validate ITDB, a prototype ITDB system is designed and implemented. The prototype is a seamless integration of five major subsystems, namely the Malicious Transaction Detection subsystem, the Attack Recovery subsystem, the Attack Isolation subsystem, the Damage Containment subsystem, and the Self-Stabilization subsystem. Extensive evaluation of the prototype based on practical database applications, simulated workload and injected attacks is done. Preliminary testing measurements suggest that when the accuracy of the intrusion detector is satisfactory, ITDB can effectively tolerate database intrusions with reasonable performance penalty.
- [Show abstract] [Hide abstract]
ABSTRACT: Concurrency control (CC) algorithms guarantee the correctness and consistency criteria for concurrent execution of a set of transactions in a database. A precondition that is seen in many CC algorithms is that the writeset (WS) and readset (RS) of transactions should be known before the transaction execution. However, in real operational environments, we know the WS and RS only for a fraction of transaction set before execution. However, optional knowledge about WS and RS of transactions is one of the advantages of the proposed CC algorithm in this paper. If the WS and RS are known before the transaction execution, the proposed algorithm will use them to improve the concurrency and performance. On the other hand, the concurrency control algorithms often use a specific static or dynamic equation in making decision about granting a lock or detection of the winner transaction. The proposed algorithm in this paper uses an adaptive resonance theory (ART)-based neural network for such a decision making. In this way, a parameter called health factor (HF) is defined for transactions that is used for comparing the transactions and detecting the winner one in accessing the database objects. HF is calculated using ART2 neural network. Experimental results show that the proposed neural-based CC (NCC) algorithm increases the level of concurrency by decreasing the number of aborts. The performance of proposed algorithm is compared with strict two-phase locking (S2PL) algorithm, which has been used in most commercial database systems. Simulation results show that the performance of proposed NCC algorithm, in terms of number of aborts, is better than S2PL algorithm in different transaction rates.Neural Computing and Applications 01/2011; 22(1). DOI:10.1007/s00521-011-0691-6 · 1.57 Impact Factor
- [Show abstract] [Hide abstract]
ABSTRACT: Concurrency control is the activity of synchronizing operations issued by concurrent executing transactions on a shared database. The aim of this control is to provide an execution that has the same effect as a serial (non-interleaved) one. The optimistic concurrency control technique allows the transactions to execute without synchronization, relying on commit-time validation to ensure serializability. Effectiveness of the optimistic techniques depends on the conflict rate of transactions. Since different systems have various patterns of conflict and the patterns may also change over time, so applying the optimistic scheme to the entire system results in degradation of performance. In this paper, a novel algorithm is proposed that dynamically selects the optimistic or pessimistic approach based on the value of conflict rate. The proposed algorithm uses an adaptive resonance theory–based neural network in making decision for granting a lock or detection of the winner transaction. In addition, the parameters of this neural network are optimized by a modified gravitational search algorithm. On the other hand, in the real operational environments we know the writeset (WS) and readset (RS) only for a fraction of transactions set before execution. So, the proposed algorithm is designed based on optional knowledge about WS and RS of transactions. Experimental results show that the proposed hybrid concurrency control algorithm results in more than 35 % reduction in the number of aborts in high-transaction rates as compared to strict two-phase locking algorithm that is used in many commercial database systems. This improvement is 13 % as compared to pure-pessimistic approach and is more than 31 % as compared to pure-optimistic approach.Neural Computing and Applications 11/2013; 23(6). DOI:10.1007/s00521-012-1147-3 · 1.57 Impact Factor