An intelligent hybrid optimistic/pessimistic concurrency control algorithm for centralized database systems using modified GSA-optimized ART neural model

Sheikhan, Mansour; Ahmadluei, Saeed

doi:10.1007/s00521-012-1147-3

Cited by 7 publications

(5 citation statements)

References 65 publications

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“…While other researchers discussed a combined classification of concurrency control algorithms in the form of performance advantages of hybrid concurrency control algorithms such as the suitability of the multi-version two-phase locking algorithm for environments that are inbetween update and read intensities (Carey and Muhanna, 1986). Hybrid algorithmic approaches that combine advantageous characteristics of optimistic and pessimistic approach strategies for concurrency control are presented by Moiz (2015) and Sheikhan and Ahmadluei (2013). The former paper introduces a hybrid concurrency control algorithm for mobile DBSs in which concurrency access anomalies are addressed depending on a variable transactions priority parameter.…”

Section: Related Workmentioning

confidence: 99%

“…Alternatively, the nearest methods to the approach presented were characterized by two works, each presenting a partial aspect of our strategy and only to some extent. The first one of these researches introduces the concept of using more than one algorithm within a hybrid intelligent concurrency control algorithm for centralized DBSs, but it only alternates between optimistic and pessimistic approaches to manage concurrency depending on the conflict rate value (Sheikhan and Ahmadluei, 2013). The second research discusses transaction priority within a hybrid concurrency control algorithm for mobile DBSs in which concurrency access anomalies are addressed depending on a variable transactions priority parameter (Moiz, 2015).…”

Section: Challenges and Performance Testingmentioning

confidence: 99%

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A two-part multi-algorithm concurrency control optimization strategy for distributed database systems

Shebka¹

2022

Int. j. adv. appl. sci.

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In this paper, we propose a novel holistic approach to address the issues of concurrency control after an exhaustive examination of the problem and the various forms it can transpire. The proposed strategy was formulated depending on different perspectives that are based on exploring a wide range of algorithms, methods, and strategies proposed in practice and theory that attempted to address the problem and its forms, but only partially succeeded in doing so. Here we proposed a two-part holistic strategy to optimize concurrency control in distributed environments that address a wide range of concurrency control anomalies by taking advantage of several concurrency control algorithms' strengths while minimizing their weaknesses. The novelty of our approach transpires from two interconnected parts that can be applied regardless of the type of distributed database environment. The first is a structured tier-based data classification system based on data sensitivity with respect to serializability requirements and ranges from strict to very relaxed forms of serializability constraints. The second is a concurrency management algorithm that allocates the appropriate concurrency control algorithm to each transaction depending on the type of transaction and/or type of data being accessed from the aforementioned tier-based classification method. Our proposed method also incorporates a priority allocation mechanism within the concurrency management algorithm. Priority is allocated to different tier transactions depending on the tier's level, which in turn reflects data importance and sensitivity. Although our proposed strategy remains an algorithmic approach as we encountered various challenges regarding performance testing of a novel multi-algorithm approach for handling concurrency control in distributed database systems. However, future work involves testing the performance of our proposed strategy either through real-time systems after considerable adjustments or by constructing an appropriate customized simulation framework. Finally, the potentials of the strategy presented here are very promising, hence, we recommend as we are also optimistic that other scholars are encouraged to further exploit the concept of using multiple concurrency control algorithms within the same distributed database environment.

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Section: Related Workmentioning

confidence: 99%

Section: Challenges and Performance Testingmentioning

confidence: 99%

A two-part multi-algorithm concurrency control optimization strategy for distributed database systems

Shebka¹

2022

Int. j. adv. appl. sci.

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“…Adaptive runtime techniques for choosing between optimistic and pessimistic synchronization protocols for every transaction are described by [28,30].…”

Section: Related Workmentioning

confidence: 99%

Composing concurrency control

Ziv

Aiken

Golan-Gueta

et al. 2015

Proceedings of the 36th ACM SIGPLAN Conference on Programming Language Design and Implementation

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Concurrency control poses significant challenges when composing computations over multiple data-structures (objects) with different concurrency-control implementations. We formalize the usually desired requirements (serializability, abort-safety, deadlock-safety, and opacity) as well as stronger versions of these properties that enable composition. We show how to compose protocols satisfying these properties so that the resulting combined protocol also satisfies these properties. Our approach generalizes well-known protocols (such as two-phase-locking and two-phase-commit) and leads to new protocols. We apply this theory to show how we can safely compose optimistic and pessimistic concurrency control. For example, we show how we can execute a transaction that accesses two objects, one controlled by an STM and another by locking.

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“…But executing transactions concurrently without control will cause problems like deadlock and inconsistency. A number of concurrency control algorithms (CC for short) [1][2][3][4][5] have been proposed to solve this kind of problem, which can guarantee the consistency and integrity of database while executing transactions.…”

Section: Introductionmentioning

confidence: 99%

“…The authors of [4] improved NCC algorithm and proposed hybrid concurrency control (HCC for short) algorithm. This algorithm counted the average situation of last 12 minutes' conflicts only, which cannot represent the conflict probability of current moment.…”

Section: Introductionmentioning

confidence: 99%

An Adaptive Decision Concurrency Control Algorithm

Chen

Zhuang

2014

AMR

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For the lack of adaptability about the existing concurrency control algorithms, adaptive decision concurrency control algorithm is proposed. ADCC algorithm divides concurrency control process into two phases in: execution authorizing phase and strategy selecting phase. In execution authorizing phase, algorithm compares statistics and effectiveness of transactions to determine the execution order of conflict transactions. In strategy selecting phase, according to transactions’ read/write status and current conflict rate, algorithm selects optimistic/pessimistic conflict resolution strategy adaptively. Such selection mechanism makes ADCC algorithm have high efficiency no matter database system is busy or idle. Simulation experiment proves that ADCC algorithm this paper proposed is superior to classical strict two phases locking algorithm and hybrid concurrency control. So ADCC algorithm performs well in the period of concurrency control.

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An intelligent hybrid optimistic/pessimistic concurrency control algorithm for centralized database systems using modified GSA-optimized ART neural model

Cited by 7 publications

References 65 publications

A two-part multi-algorithm concurrency control optimization strategy for distributed database systems

A two-part multi-algorithm concurrency control optimization strategy for distributed database systems

Composing concurrency control

An Adaptive Decision Concurrency Control Algorithm

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