Type of Document Dissertation Author Yu, Qi Author's Email Address email@example.com 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 Keywords
- Service Computing
- Query Optimization
- Skyline Computation
- Quality of Web Service
Date of Defense 2008-07-30 Availability unrestricted AbstractIn 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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