Behavior of database production rules: termination, confluence, and observable determinism
SIGMOD '92 Proceedings of the 1992 ACM SIGMOD international conference on Management of data
Termination and confluence of rule execution
CIKM '93 Proceedings of the second international conference on Information and knowledge management
A simulation-based study on the concurrent execution of rules in a database environment
Journal of Parallel and Distributed Computing
Static analysis techniques for predicting the behavior of active database rules
ACM Transactions on Database Systems (TODS)
Termination and confluence of active rules in active object databases
Termination and confluence of active rules in active object databases
FRAMBOISE—an approach to framework-based active database management system construction
Proceedings of the seventh international conference on Information and knowledge management
Concurrent rule execution in active databases
Information Systems
Distributed events in active database systems: letting the genie out of the bottle
Data & Knowledge Engineering - Special jubilee issue: DKE 25
The TriGS active object-oriented database system— an overview
ACM SIGMOD Record
ACM Computing Surveys (CSUR)
Journal of Intelligent Information Systems
An algebraic approach to static analysis of active database rules
ACM Transactions on Database Systems (TODS)
Introductory Discrete Mathematics
Introductory Discrete Mathematics
An Algebraic Approach to Rule Analysis in Expert Database Systems
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
NAOS - Efficient and Modular Reactive Capabilities in an Object-Oriented Database System
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
An Execution and Transaction Model for Active, Rule-Based Component Integration Middleware
EDCIS '02 Proceedings of the First International Conference on Engineering and Deployment of Cooperative Information Systems
The IRules Project - Using Active Rules for the Integration of Distributed Software Components
Proceedings of the IFIP TC2/WG2.6 Ninth Working Conference on Database Semantics: Semantic Issues in E-Commerce Systems
Deriving Active Rules for Workflow Enactment
DEXA '96 Proceedings of the 7th International Conference on Database and Expert Systems Applications
ECA Rule Support for Distributed Heterogeneous Environments
ICDE '98 Proceedings of the Fourteenth International Conference on Data Engineering
Abstract Interpretation of Active Rules and its Use in Termination Analysis
ICDT '97 Proceedings of the 6th International Conference on Database Theory
WIDE-a distributed architecture for workflow management
RIDE '97 Proceedings of the 7th International Workshop on Research Issues in Data Engineering (RIDE '97) High Performance Database Management for Large-Scale Applications
An architecture and execution environment for component integration rules
An architecture and execution environment for component integration rules
Management of composite event for active database rule scheduling
IRI'09 Proceedings of the 10th IEEE international conference on Information Reuse & Integration
The evolution of conceptual modeling
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The use of rules in a distributed environment creates new challenges for the development of active rule execution models. In particular, since a single event can trigger multiple rules that execute over distributed sources of data, it is important to make use of concurrent rule execution whenever possible. This paper presents the details of the integration rule scheduling (IRS) algorithm. Integration rules are active database rules that are used for component integration in a distributed environment. The IRS algorithm identifies rule conflicts for multiple rules triggered by the same event through static, compile-time analysis of the read and write sets of each rule. A unique aspect of the algorithm is that the conflict analysis includes the effects of nested rule execution that occurs as a result of using an execution model with an immediate coupling mode. The algorithm therefore identifies conflicts that may occur as a result of the concurrent execution of different rule triggering sequences. The rules are then formed into a priority graph before execution, defining the order in which rules triggered by the same event should be processed. Rules with the same priority can be executed concurrently. The IRS algorithm guarantees confluence in the final state of the rule execution. The IRS algorithm is applicable for rule scheduling in both distributed and centralized rule execution environments.