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

Bounded Inconsistency for Type-Specific Concurrency Control

The traditional correctness criterion of serializability in databases is considered too restrictive especially when databases are used to model advanced applications. In general, two approaches are adopted to address this problem. The first approach considers placing more structure on data objects to exploit type specific properties while keeping serializability as the correctness criterion. The other approach uses explicit semantics of transactions and databases to permit interleaved executions of transactions that are non-serializable. In this paper, we attempt to bridge the gap between the two approaches by using the notion of serializability with bounded inconsistency. Users are free to specify the maximumlevel of inconsistency that can be allowed in the executions of operations dynamically. In particular, if no inconsistency is allowed in the execution of any operation, the protocol will be reduced to a standard strict two phase locking protocol based on type-specific semantics of..