Supporting data consistency in concurrent process execution with assurance points and invariants

  • Authors:

  • Susan D. Urban;Andrew Courter;Le Gao;Mary Shuman

  • Affiliations:

  • Department of Industrial Engineering, Texas Tech University, Lubbock, TX;Department of Computer Science, Texas Tech University, Lubbock, TX;Department of Computer Science, Texas Tech University, Lubbock, TX;Department of Computer Science, University of North Carolina, Charlotte, Charlotte, NC

  • Venue:
  • RuleML'11 Proceedings of the 5th international conference on Rule-based modeling and computing on the semantic web
  • Year:
  • 2011

Quantified Score

Hi-index 0.00

Visualization

Abstract

This research has developed the concept of invariant rules for monitoring data in a service-oriented environment that allows concurrent data accessibility with relaxed isolation. The invariant rule approach is an extension of the assurance point concept, where an assurance point is a logical and physical checkpoint that is used to store critical data values and to check pre and post conditions related to service execution. Invariant rules provide a stronger way of monitoring constraints and guaranteeing that a condition holds for a specific duration of execution as defined by starting and ending assurance points, using the change notification capabilities of Delta-Enabled Grid Services. This paper outlines the specification of invariant rules as well as the invariant monitoring system for activating invariants, evaluating invariant rule conditions, and deactivating invariants. The system is supported by an invariant evaluation web service that uses materialized views for more efficient re-evaluation of invariant rule conditions. The research includes a performance analysis of the invariant evaluation Web Service. The strength of the invariant rule technique is that it provides a way to monitor data consistency in an environment where the coordinated locking of data items across multiple service executions is not possible.