scholarly journals Transformation of Ontological Represented Web Service Composition Problem into a Planning One

2011 ◽  
Vol 11 (2) ◽  
Author(s):  
Zoltán Ďurčík ◽  
Ján Paralič
Author(s):  
Arion de Campos Jr. ◽  
Aurora T. R. Pozo ◽  
Silvia R. Vergilio

The Web service composition refers to the aggregation of Web services to meet customers' needs in the construction of complex applications. The selection among a large number of Web services that provide the desired functionalities for the composition is generally driven by QoS (Quality of Service) attributes, and formulated as a constrained multi-objective optimization problem. However, many equally important QoS attributes exist and in this situation the performance of the multi-objective algorithms can be degraded. To deal properly with this problem we investigate in this chapter a solution based in many-objective optimization algorithms. We conduct an empirical analysis to measure the performance of the proposed solution with the following preference relations: Controlling the Dominance Area of Solutions, Maximum Ranking and Average Ranking. These preference relations are implemented with NSGA-II using five objectives. A set of performance measures is used to investigate how these techniques affect convergence and diversity of the search in the WSC context.


2012 ◽  
Vol 9 (2) ◽  
pp. 1-20 ◽  
Author(s):  
Pablo Rodriguez-Mier ◽  
Manuel Mucientes ◽  
Juan C. Vidal ◽  
Manuel Lama

The ability of web services to build and integrate loosely-coupled systems has attracted a great deal of attention from researchers in the field of the automatic web service composition. The combination of different web services to build complex systems can be carried out using different control structures to coordinate the execution flow and, therefore, finding the optimal combination of web services represents a non-trivial search effort. Furthermore, the time restrictions together with the growing number of available services complicate further the composition problem. In this paper the authors present an optimal and complete algorithm which finds all valid compositions from the point of view of the semantic input-output message structure matching. Given a request, a service dependency graph which represents a suboptimal solution is dynamically generated. Then, the solution is improved using a backward heuristic search based on the A* algorithm which finds all the possible solutions with different number of services and runpath. Moreover, in order to improve the scalability of our approach, a set of dynamic optimization techniques have been included. The proposal has been validated using eight different repositories from the Web Service Challenge 2008, obtaining all optimal solutions with minimal overhead.


2011 ◽  
Vol 268-270 ◽  
pp. 1415-1420
Author(s):  
Xian Wen Fang ◽  
Ying Hua Feng ◽  
Zhi Xiang Yin

With the development of Web service theories and technologies, it has been an effective approach to satisfy users’ requirements by service composition. For independent global constraints Web services composition problem, the paper presents an optimization method of Web service composition with constraint using fuzzy Petri net(FPN), which can transforms solving the optimal service composition problem into locating the largest trust value of legal firing sequences in the FPN model. Then we use the cooperative algorithm including simulated annealing and genetic algorithm (SAGA) to find the optimal legal sequences. The experimental results show that the method can not only reduce the time cost, but also find more feasible solutions.


2021 ◽  
Author(s):  
◽  
Alexandre Sawczuk da Silva

<p>Automated Web service composition is one of the holy grails of service-oriented computing, since it allows users to create an application simply by specifying the inputs the resulting application should require, the outputs it should produce, and any constraints it should observe. The composition problem has been handled using a variety of techniques, from AI planning to optimisation algorithms, however no work so far has focused on handling multiple composition facets simultaneously, producing solutions that: (1) are fully functional (i.e. fully executable, with semantically-matched inputs and outputs), (2) employ a variety of composition constructs (e.g. sequential, parallel, and choice constructs), and (3) are optimised according to non-functional Quality of Service (QoS) measurements. The overall goal of this thesis is to propose hybrid Web service composition approaches that consider elements from all three facets described above when generating solutions. These approaches combine elements of AI planning and of Evolutionary Computation to allow for the creation of compositions that meet all of these requirements.  Firstly, this thesis proposes two novel approaches for Web service composition with direct representations. The first one is a tree-based approach where the leaf nodes are the atomic services included in the composition and the inner nodes are the structural constructs that shape the composition workflow. The second one is a graph-based approach where the atomic services are the vertices and the edges connecting them form the composition workflow. The two approaches are compared to determine which is most suitable to the QoS-aware fully automated Web service composition problem.  Secondly, this thesis proposes novel sequence-based approaches for Web service composition that use an indirect representation, i.e. they encode solutions as sequences of services. By representing solutions in this way, it is possible to initialise and evolve them without having to enforce their functional correctness. Then, before evaluating the fitness of each solution, a decoding algorithm is used to transform the sequence into the corresponding composition. The decoding algorithm builds the workflow using the ordering in the sequence as closely as possible when selecting the next service to be added, while at the same time generating a functionally correct structure.  Thirdly, this thesis treats Web service composition as a multi-objective problem, generating a set of trade-off solutions the user can choose from. More specifically, it proposes multi-objective approaches to fully automated Web service composition, which means that conflicting QoS attributes are independently optimised using a variety of representations that support flexible workflow structures. Additionally, a multi-objective and fully automated memetic approach that uses a local search operator to further improve the quality of solutions is proposed.  The following major contributions have been made in this thesis. Firstly, two approaches for Web service composition with direct representations were proposed. When the choice construct is not considered, the graph-based approach produces solutions of higher quality than those of the tree-based approach, but the opposite is true when the choice construct is included. Secondly, indirect representation approaches for Web service composition were proposed. These approaches perform well and can produce solutions with better quality than those found by the graph-based approach. Finally, we propose multi-objective approaches to fully automated service composition, employing different problem representations and a local search operator. The multi-objective approaches using the sequence-based representation were found to produce solutions with better overall quality.</p>


2013 ◽  
Vol 28 (2) ◽  
pp. 137-156 ◽  
Author(s):  
Ourania Hatzi ◽  
Dimitris Vrakas ◽  
Nick Bassiliades ◽  
Dimosthenis Anagnostopoulos ◽  
Ioannis Vlahavas

AbstractThis paper presents PORSCE II, an integrated system that performs automatic Semantic Web service composition exploiting artificial intelligence (AI) techniques, specifically planning. Essential steps in achieving Web service composition include the translation of the Web service composition problem into a solver-ready planning domain and problem, followed by the acquisition of solutions, and the translation of the solutions back to Web service terms. The solutions to the problem, that is, the descriptions of the desired composite service, are obtained by means of external domain-independent planning systems, they are visualized and finally evaluated. Throughout the entire process, the system exploits semantic information extracted from the semantic descriptions of the available Web services and the corresponding ontologies, in order to perform composition under semantic awareness and relaxation.


2015 ◽  
Vol 24 (01) ◽  
pp. 1450015 ◽  
Author(s):  
Ourania Hatzi ◽  
Mara Nikolaidou ◽  
Dimitris Vrakas ◽  
Nick Bassiliades ◽  
Dimosthenis Anagnostopoulos ◽  
...  

Web service composition is a significant problem as the number of available web services increases; however, manual composition is not an efficient option. Automated web service composition can be performed using AI Planning techniques, utilizing descriptions of available atomic web services, enhanced with semantic awareness and relaxation. This paper discusses a unified, semantically aware approach, handling both semantic (OWL-S & SAWSDL) and non-semantic (WSDL) web service descriptions. In the first case, ontology analysis is adopted to semantically enhance the planning domains and problems, in order to deal with cases where exact syntactic input-to-output matching is not feasible. In the non-semantic descriptions case, semantic information is acquired utilizing alternative sources such as lexical thesauri. Concept similarity measures are applied and utilized to achieve the desired degree of semantic relaxation. The solution to a web service composition problem is a plan describing the desired composite service. To support the proposed approach, the PORSCE framework has been implemented. The framework is modular, integrating discrete web service description languages and semantic relaxation techniques. Based on the similarity measures suggested in the paper, performance issues are also explored.


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