The Design and Implementation of a Self-Healing Database System

Liu, Peng; Jing, Jiwu; Luenam, Pramote; Wang, Ying; Li, Lunquan; Ingsriswang, Supawadee

doi:10.1023/b:jiis.0000047394.02444.8d

Cited by 30 publications

(18 citation statements)

References 41 publications

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“…Oracle DBMS does not log read operations in defaulted installations. Existing methods either construct read logs [8] [9] or maintain an inter-transaction dependencies at runtime [10]. In order to build recovery from malicious transactions, transaction logging methods first analyzed transaction dependencies in the history.…”

Section: Transaction Logging Methodsmentioning

confidence: 99%

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Data Dependency Based Recovery Approaches in Survival Database Systems

Zheng

Qin

Sun

2007

Computational Science – ICCS 2007

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Abstract.Recovering from malicious attacks in survival database systems is vital in mission-critical information systems. Traditional rollback and reexecute techniques are too time-consuming and can not be applied in survival environments. In this paper, two efficient approaches -transaction dependency based and data dependency based are proposed. Comparing to transaction dependency based approach, data dependency recovery approaches need not undo innocent operations in malicious and affected transactions even some benign blind writes on bad data item speed up recovery process.

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Section: Transaction Logging Methodsmentioning

confidence: 99%

“…First ODAM [8] then ITDB [9] and Phoenix [10] are survival DBMSs developed by Peng Liu et al and Tzi-cher Chiueh respectively. These prototypes are implemented on top of a COTS (Commercial-Off-The-Shelf) DBMS, e.g.…”

Section: Related Workmentioning

confidence: 99%

Data Dependency Based Recovery Approaches in Survival Database Systems

Zheng

Qin

Sun

2007

Computational Science – ICCS 2007

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“…Physical database tuning and the use of self-healing performance tuning methodologies were introduced in [11] [12]. In [13], an modular approach was presented for providing self-healing database functionalities.…”

Section: Regression Analysismentioning

confidence: 99%

An Adaptive Hybrid Controller for DBMS Performance Tuning

Fattah¹,

Mahmoud²,

Abd-Elmegid³

2014

IJACSA

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Abstract-Performance tuning process of database management system (DBMS) is an expensive, complex and time consuming process to be handled by human experts. A proposed adaptive controller is developed that utilizes a hybrid model from fuzzy logic and regression analysis to tune the memory-resident data structures of DBMS. The fuzzy logic module uses flexible rule matrix with adaption techniques to deal with fluctuations and abrupt changes in the operation environment. The regression module predicts fluctuations in operation environment so the controller can take former action. Experimental results on standard benchmarks showed significant performance enhancement as compared to builtin self-tuning features.

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“…Several methods have been proposed that proactively monitor the system performance indicators analyze the symptoms and auto tune the DBMS to deliver enhanced performance. Use of Materialized views and Indexes, Pruning table and column sets [1][2], use of self healing techniques [3][4], use of physical design tuning are among the proposed solutions. The classical control is modified and a three stage control involving Monitor, Analyze and Tune [5] is employed to ensure system stability.…”

Section: Related Workmentioning

confidence: 99%

Fuzzy Controlled Architecture for Performance Tuning of Database Management System

Rodd¹,

Kulkarni²,

Yardi³

2012

IJCA

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Database Management Systems deliver higher performance only when they are properly tuned. Database tuning is complicated due to the fact that several conflicting tuning parameters have to be adjusted simultaneously for a variety of workload types and the highly unpredictable traffic patterns. The Database Administrator(DBA) has to be an expert and using his experience and expertise must judiciously decide the extent of tuning of the most important tuning factors so as to ensure the required level of performance in terms of response time and throughput. The process of tuning being complex and to keep the cost of ownership low, it is desirable to build self tuning database systems. In this paper, a new tuning architecture based on fuzzy logic is presented, where in, the control action is expressed in linguistic terms. In this system the key performance indicators are fuzzified, appropriate fuzzy rules are employed to estimate the extent of tuning required for a few important tuning parameters. After defuzzification, a control action is initiated to scale up the system performance. The experimental results obtained for different workload types and the user load, indicate that it is possible to significantly improve the query response time using this technique.

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The Design and Implementation of a Self-Healing Database System

Cited by 30 publications

References 41 publications

Data Dependency Based Recovery Approaches in Survival Database Systems

Data Dependency Based Recovery Approaches in Survival Database Systems

An Adaptive Hybrid Controller for DBMS Performance Tuning

Fuzzy Controlled Architecture for Performance Tuning of Database Management System

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