Title page for ETD etd-08052008-122556

Type of Document Dissertation
Author Yu, Qi
Author's Email Address qyu@vt.edu
URN etd-08052008-122556
Title A Foundational Framework for Service Query Optimization
Degree PhD
Department Computer Science
Advisory Committee
Advisor Name Title
Gracanin, Denis Committee Chair
Bouguettaya, Athman Committee Co-Chair
Barkhi, Reza Committee Member
Bohner, Shawn A. Committee Member
Lu, Chang-Tien Committee Member
  • Service Computing
  • Query Optimization
  • Skyline Computation
  • Quality of Web Service
Date of Defense 2008-07-30
Availability unrestricted
In this dissertation, we present a novel foundational framework that lays out a theoretical underpinning for the emerging services science. The proposed framework provides disciplined and systematic support for efficient access to Web services' functionalities. The key components of the proposed framework centers around a novel service model that provides a formal abstraction of the Web services within an application domain. A service calculus and a service algebra are defined to facilitate users in accessing services via declarative service queries. We provide the implementation of the service algebra. This enables the generation of Service Execution Plans (SEPs) that can be used by users to directly access services. We present an optimization algorithm to efficiently select the SEPs with the best QoWS.

We then propose a multi-objective optimization approach that releases users from the tedious weight assigning process.

We develop service skyline computation techniques that return a set of most interesting SEPs. The service skyline guarantees to include the user desired SEPs. We further explore a set of novel heuristics for computing service skylines over sets of services. This enables users to efficiently and optimally access multiple services simultaneously as an integrated service package. Finally, we consider the performance fluctuation of service providers due to the dynamic service environment. We propose an uncertain QoWS model and a novel concept called p-dominant service skyline. We develop new indexing structures and algorithms to efficiently compute the p-dominant service skyline. We derive analytical models and conduct extensive sets of experiments to evaluate the proposed framework and service query optimization algorithms.

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