Execution Autonomy in Distributed Transaction Processing

We study the feasibility of execution autonomy in systems with asynchronous transaction processing based on epsilon-serializability (ESR). The abstract correctness criteria defined by ESR are implemented by techniques such as asynchronous divergence control and asynchronous consistency restoration. Concrete application examples in a distributed environment, such as banking, are described in order to illustrate the advantages of using ESR to support execution autonomy

Revisiting epsilon serializabilty to improve the database state machine

Recently, a large body of research has been exploiting group communication based techniques to improve the dependability and performance of synchronously replicated database systems

A comparative study of transaction management services in multidatabase heterogeneous systems

Multidatabases are being actively researched as a relatively new area in which many aspects are not yet fully understood. This area of transaction management in multidatabase systems still has many unresolved problems. The problem areas which this dissertation addresses are classification of multidatabase systems, global concurrency control, correctness criterion in a multidatabase environment, global deadlock detection, atomic commitment and crash recovery. A core group of research addressing these problems was identified and studied. The dissertation contributes to the multidatabase transaction management topic by introducing an alternative classification method for such multiple database systems; assessing existing research into transaction management schemes and based on this assessment, proposes a transaction processing model founded on the optimal properties of transaction management identified during the course of this research.ComputingM. Sc. (Computer Science

Research issues in real-time database systems

Cataloged from PDF version of article.Today's real-time systems are characterized by managing large volumes of data. Efficient database management algorithms for accessing and manipulating data are required to satisfy timing constraints of supported applications. Real-time database systems involve a new research area investigating possible ways of applying database systems technology to real-time systems. Management of real-time information through a database system requires the integration of concepts from both real-time systems and database systems. Some new criteria need to be developed to involve timing constraints of real-time applications in many database systems design issues, such as transaction/query processing, data buffering, CPU, and IO scheduling. In this paper, a basic understanding of the issues in real-time database systems is provided and the research efforts in this area are introduced. Different approaches to various problems of real-time database systems are briefly described, and possible future research directions are discussed

Integrating Transaction Services into Web-based Software Development Environments

Software Development Environments (SDE) require sophisticated database transaction models due to the long-duration,interactive, and cooperative nature of the software engineering activities. Such Extended Transaction Models (ETM) have been proposed and implemented by building application-specific databases for the SDEs. With the development of World Wide Web (WWW), there have been a number of efforts to build SDEs on top of the WWW. Using web servers as the databases to store the software artifacts provided us with a new challenge: how to implement the ETMs in such web-based SDEs without requiring the web servers to be customized specifically according to the application domains of the SDEs. This paper presents our experiences of integrating transaction services into web based SDEs. We evolved from the traditional approach of building a transaction management component that operated on top of a dedicated database to the external transaction server approach. A transaction server, called JPernLite, was built to operate independently of the web servers and provide the necessary extensibility for SDEs to implement their ETMs. The transaction server can be integrated into the SDE via a number of interfaces, and we discuss the pros and cons of each alternative in detail

Performance characteristics of semantics-based concurrency control protocols.

by Keith, Hang-kwong Mak.Thesis (M.Phil.)--Chinese University of Hong Kong, 1995.Includes bibliographical references (leaves 122-127).Abstract --- p.iAcknowledgement --- p.iiiChapter 1 --- Introduction --- p.1Chapter 2 --- Background --- p.4Chapter 2.1 --- Read/Write Model --- p.4Chapter 2.2 --- Abstract Data Type Model --- p.5Chapter 2.3 --- Overview of Semantics-Based Concurrency Control Protocols --- p.7Chapter 2.4 --- Concurrency Hierarchy --- p.9Chapter 2.5 --- Control Flow of the Strict Two Phase Locking Protocol --- p.11Chapter 2.5.1 --- Flow of an Operation --- p.12Chapter 2.5.2 --- Response Time of a Transaction --- p.13Chapter 2.5.3 --- Factors Affecting the Response Time of a Transaction --- p.14Chapter 3 --- Semantics-Based Concurrency Control Protocols --- p.16Chapter 3.1 --- Strict Two Phase Locking --- p.16Chapter 3.2 --- Conflict Relations --- p.17Chapter 3.2.1 --- Commutativity (COMM) --- p.17Chapter 3.2.2 --- Forward and Right Backward Commutativity --- p.19Chapter 3.2.3 --- Exploiting Context-Specific Information --- p.21Chapter 3.2.4 --- Relaxing Correctness Criterion by Allowing Bounded Inconsistency --- p.26Chapter 4 --- Related Work --- p.32Chapter 4.1 --- Exploiting Transaction Semantics --- p.32Chapter 4.2 --- Exploting Object Semantics --- p.34Chapter 4.3 --- Sacrificing Consistency --- p.35Chapter 4.4 --- Other Approaches --- p.37Chapter 5 --- Performance Study (Testbed Approach) --- p.39Chapter 5.1 --- System Model --- p.39Chapter 5.1.1 --- Main Memory Database --- p.39Chapter 5.1.2 --- System Configuration --- p.40Chapter 5.1.3 --- Execution of Operations --- p.41Chapter 5.1.4 --- Recovery --- p.42Chapter 5.2 --- Parameter Settings and Performance Metrics --- p.43Chapter 6 --- Performance Results and Analysis (Testbed Approach) --- p.46Chapter 6.1 --- Read/Write Model vs. Abstract Data Type Model --- p.46Chapter 6.2 --- Using Context-Specific Information --- p.52Chapter 6.3 --- Role of Conflict Ratio --- p.55Chapter 6.4 --- Relaxing the Correctness Criterion --- p.58Chapter 6.4.1 --- Overhead and Performance Gain --- p.58Chapter 6.4.2 --- Range Queries using Bounded Inconsistency --- p.63Chapter 7 --- Performance Study (Simulation Approach) --- p.69Chapter 7.1 --- Simulation Model --- p.70Chapter 7.1.1 --- Logical Queueing Model --- p.70Chapter 7.1.2 --- Physical Queueing Model --- p.71Chapter 7.2 --- Experiment Information --- p.74Chapter 7.2.1 --- Parameter Settings --- p.74Chapter 7.2.2 --- Performance Metrics --- p.75Chapter 8 --- Performance Results and Analysis (Simulation Approach) --- p.76Chapter 8.1 --- Relaxing Correctness Criterion of Serial Executions --- p.77Chapter 8.1.1 --- Impact of Resource Contention --- p.77Chapter 8.1.2 --- Impact of Infinite Resources --- p.80Chapter 8.1.3 --- Impact of Limited Resources --- p.87Chapter 8.1.4 --- Impact of Multiple Resources --- p.89Chapter 8.1.5 --- Impact of Transaction Type --- p.95Chapter 8.1.6 --- Impact of Concurrency Control Overhead --- p.96Chapter 8.2 --- Exploiting Context-Specific Information --- p.98Chapter 8.2.1 --- Impact of Limited Resource --- p.98Chapter 8.2.2 --- Impact of Infinite and Multiple Resources --- p.101Chapter 8.2.3 --- Impact of Transaction Length --- p.106Chapter 8.2.4 --- Impact of Buffer Size --- p.108Chapter 8.2.5 --- Impact of Concurrency Control Overhead --- p.110Chapter 8.3 --- Summary and Discussion --- p.113Chapter 8.3.1 --- Summary of Results --- p.113Chapter 8.3.2 --- Relaxing Correctness Criterion vs. Exploiting Context-Specific In- formation --- p.114Chapter 9 --- Conclusions --- p.116Bibliography --- p.122Chapter A --- Commutativity Tables for Queue Objects --- p.128Chapter B --- Specification of a Queue Object --- p.129Chapter C --- Commutativity Tables with Bounded Inconsistency for Queue Objects --- p.132Chapter D --- Some Implementation Issues --- p.134Chapter D.1 --- Important Data Structures --- p.134Chapter D.2 --- Conflict Checking --- p.136Chapter D.3 --- Deadlock Detection --- p.137Chapter E --- Simulation Results --- p.139Chapter E.l --- Impact of Infinite Resources (Bounded Inconsistency) --- p.140Chapter E.2 --- Impact of Multiple Resource (Bounded Inconsistency) --- p.141Chapter E.3 --- Impact of Transaction Type (Bounded Inconsistency) --- p.142Chapter E.4 --- Impact of Concurrency Control Overhead (Bounded Inconsistency) --- p.144Chapter E.4.1 --- Infinite Resources --- p.144Chapter E.4.2 --- Limited Resource --- p.146Chapter E.5 --- Impact of Resource Levels (Exploiting Context-Specific Information) --- p.149Chapter E.6 --- Impact of Buffer Size (Exploiting Context-Specific Information) --- p.150Chapter E.7 --- Impact of Concurrency Control Overhead (Exploiting Context-Specific In- formation) --- p.155Chapter E.7.1 --- Impact of Infinite Resources --- p.155Chapter E.7.2 --- Impact of Limited Resources --- p.157Chapter E.7.3 --- Impact of Transaction Length --- p.160Chapter E.7.4 --- Role of Conflict Ratio --- p.16