George Baryannis
(For an up-to-date profile and publications, please visit https://www.researchgate.net/profile/George_Baryannis). I am Senior Lecturer in Artificial Intelligence at the University of Huddersfield and a member of the Centre for Planning, Autonomy and Representation of Knowledge (PARK). I received a Dipl.Eng. in Electronic and Computer Engineering from the Technical University of Crete, Greece and a M.Sc. and Ph.D. in Computer Science from the University of Crete, Greece. I have over 10 years of experience in research within the broader area of Artificial Intelligence and applications.
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Service specifications rely on the expression of conditions that should hold before and after service execution. Such specifications are prone to a family of problems, known in the AI literature as the frame, ramification and qualification problems. These problems deal with the succinct and flexible representation of non-effects, indirect effects and preconditions, respectively. Research in services has largely ignored these problems, at the same time ignoring their effects, such as compromising the integrity and correctness of services and service compositions and the inability to provide justification for unexpected execution results.
To address these issues, this thesis proposes the Web Service Specification Language (WSSL), a novel, semantics-aware language for the specification and composition of services, independent of service design models. WSSL's foundation is the fluent calculus, a specification language for robots that offers solutions to the frame, ramification and qualification problems. Further language extensions achieve three major goals: realize service composition via planning, supporting non-deterministic constructs, such as conditionals and loops; include specification of QoS profiles; and support partially observable service states.
To investigate WSSL's applicability and demonstrate its benefits, we analyze correctness of the composition extension, decidability and complexity of the underlying theory, as well as compatibility with other related languages in service science. Moreover, an innovative service composition and verification framework is implemented, that advances state-of-the-art by satisfying several desirable requirements simultaneously: ramifications and partial observability in service and goal modeling; non-determinism in composition schemas; dynamic binding of tasks to concrete services; explanations for unexpected behavior; QoS-awareness through pruning and ranking techniques based on heuristics and task-specific goals and an all-encompassing QoS aggregation method for global goals.
Experimental evaluation is performed using synthetically generated specifications and composition goals, investigating performance scalability in terms of execution time, as well as optimality with regard to the produced composite process. The results show that, even in the presence of ramifications in some specifications, functional planning is efficient for repositories up to 500 specifications. Also, the cost of functional discovery per single service is insignificant, hence achieving good performance even when executed for multiple candidate plans. Finally, optimality relies mainly on defining suitable problem-specific heuristics; thus, its success depends mostly on the expertise of the composition designer.
Service specifications rely on the expression of conditions that should hold before and after service execution. Such specifications are prone to a family of problems, known in the AI literature as the frame, ramification and qualification problems. These problems deal with the succinct and flexible representation of non-effects, indirect effects and preconditions, respectively. Research in services has largely ignored these problems, at the same time ignoring their effects, such as compromising the integrity and correctness of services and service compositions and the inability to provide justification for unexpected execution results.
To address these issues, this thesis proposes the Web Service Specification Language (WSSL), a novel, semantics-aware language for the specification and composition of services, independent of service design models. WSSL's foundation is the fluent calculus, a specification language for robots that offers solutions to the frame, ramification and qualification problems. Further language extensions achieve three major goals: realize service composition via planning, supporting non-deterministic constructs, such as conditionals and loops; include specification of QoS profiles; and support partially observable service states.
To investigate WSSL's applicability and demonstrate its benefits, we analyze correctness of the composition extension, decidability and complexity of the underlying theory, as well as compatibility with other related languages in service science. Moreover, an innovative service composition and verification framework is implemented, that advances state-of-the-art by satisfying several desirable requirements simultaneously: ramifications and partial observability in service and goal modeling; non-determinism in composition schemas; dynamic binding of tasks to concrete services; explanations for unexpected behavior; QoS-awareness through pruning and ranking techniques based on heuristics and task-specific goals and an all-encompassing QoS aggregation method for global goals.
Experimental evaluation is performed using synthetically generated specifications and composition goals, investigating performance scalability in terms of execution time, as well as optimality with regard to the produced composite process. The results show that, even in the presence of ramifications in some specifications, functional planning is efficient for repositories up to 500 specifications. Also, the cost of functional discovery per single service is insignificant, hence achieving good performance even when executed for multiple candidate plans. Finally, optimality relies mainly on defining suitable problem-specific heuristics; thus, its success depends mostly on the expertise of the composition designer.