Service-based situational awareness on the Semantic Web

Abstract

This research was focused on Endsley's [1] second-level situational awareness (understanding) as it applies to service-oriented information technology environments in the context of the Semantic Web. Specifically, this research addressed the problem of developing accurate situational assessments related to the status or health of IT services especially composite, dynamic IT services, when some of Endsley's [1] first level (perceived) information is inaccurate or incomplete. This research resulted in a Web Ontology Language for Services (OWL-S) and Probabilistic OWL (PR-OWL2) based ontology and an associated Multi-Entity Bayesian Network which are flexible and highly effective in calculating situational assessments through the propagation of posterior probabilities using Bayesian logic. This research (1) identifies sufficient information required for effective situational awareness reasoning, (2) specifies the predicates and semantics necessary to represent service components and dependencies, (3) applies Multi-Entity Bayesian Network to reason with situational awareness information, (4) ensures the correctness and consistency of the situational awareness ontology, and (5) accurately estimates posterior probabilities consistent with situational awareness information.