Viorica Rozina Chifu

Optimizing the Semantic Web Service Composition Process Using Cuckoo Search

The behavior of biological individuals which efficiently deal with complex life problems represents an inspiration source in the design of meta-heuristics for solving optimization problems. The Cuckoo Search is such a meta-heuristic inspired by the behavior of cuckoos in search for the appropriate nest where to lay eggs. This paper investigates how the Cuckoo Search meta-heuristic can be adapted and enhanced to solve the problem of selecting the optimal solution in semantic Web service composition. To improve the performance of the cuckoo-inspired algorithm we define a 1-OPT heuristic which expands the search space in a controlled way so as to avoid the stagnation on local optimal solutions. The search space is modeled as an Enhanced Planning Graph, dynamically built for each user request. To identify the optimal solution encoded in the graph we define a fitness function which uses the QoS attributes and the semantic quality as selection criteria. The cuckoo-inspired method has been evaluated on a set of scenarios from the trip planning domain.

Immune-inspired method for selecting the optimal solution in web service composition

This paper presents an immune-inspired algorithm applied in the context of Web service composition to select the optimal composition solution. Our approach models Web service composition as a multi-layered process which creates a planning-graph structure along with a matrix of semantic links. We have enhanced the classical planning graph with the new concepts of service cluster and semantic similarity link. The semantic similarity links are defined between services on different graph layers and are stored in a matrix of semantic links. To calculate the degree of the semantic match between services, we have adapted the information retrieval measures of recall, precision and F_Measure. The immune-inspired algorithm uses the enhanced planning graph and the matrix of semantic links to select the optimal composition solution employing the QoS attributes and the semantic quality as the selection criteria.

Fluent calculus-based Web service composition — From OWL-S to fluent calculus

Web service composition facilitates the creation of new services out of existing ones, for satisfying a complex functionality. Automatic Web service composition is considered as one of the most promising features that can be realized by Web services. This paper presents a novel approach for semantic Web service composition based on the fluent calculus. We show how the planning capabilities of the fluent calculus can be used to automatically generate a Web service composition. We have identified a mapping between an OWL-S process ontology and the fluent calculus concepts. We also present an algorithm to translate OWL-S service descriptions into an equivalent fluent calculus service specification. This specification is then forwarded as input to a flux planner to generate the plans that solve the composition goal. As a result, the solution for the requested functionality of the composed Web service is obtained. FLUX is used as the logic programming method to implement the mathematical formalism of the fluent calculus.

Ant-Inspired Technique for Automatic Web Service Composition and Selection

This paper presents a technique for semantic Web service composition inspired by the behavior of ants. The proposed technique combines a service composition graph model with the ant colony optimization met heuristic to select the optimal composition solution. In our approach, we have considered as selection criteria the QoS attributes of the services and the semantic quality of the connections between the services involved in a composition solution.

Semantic Web Service Clustering for Efficient Discovery Using an Ant-Based Method

This paper presents an ant-inspired method for clustering semantic Web services. The method considers the degree of semantic similarity between services as the main clustering criterion. To measure the semantic similarity between two services we propose a matching method and a set of metrics. The proposed metrics evaluate the degree of match between the ontology concepts describing two services. We have tested the ant-inspired clustering method on the SAWSDL-TC benchmark and we have evaluated its performance using the Dunn Index, the Intra-Cluster Variance metric and an original metric we introduce in this paper.

A graph based backward chaining method for Web service composition

This paper proposes a new method for the automatic composition of semantic Web services. The proposed method consists in constructing a graph and then searching for a sub-graph of this graph, which will represent a candidate composition solution. First, the method constructs a directed acyclic graph, which represents the functional semantics of the Web services as well as the semantic dependency between the inputs and the outputs of the services. Second, composition sub-graphs that satisfy the functionality requested by a client are searched for and ranked according to certain criteria such as user preferences and QoS. The different sub-graphs found represent different service compositions. Finally, the method selects the best service composition for a given user request. To evaluate the method, an experimental framework that automatically composes services has been implemented. The effectiveness of the method has been demonstrated by using a scenario from the trip planning domain.

Cuckoo-inspired hybrid algorithm for selecting the optimal Web service composition

This paper presents a bio-inspired hybrid algorithm that selects the optimal solution in semanticWeb service composition. The proposed algorithm combines the cuckoo search metaheuristic with evolutionary computing, reinforcement learning and tabu search to optimize the selection process in terms of execution time and explored search space. We model the search space as an Enhanced Planning Graph structure which encodes all the possible composition solutions for a given user request. To establish whether a solution is optimal, the QoS attributes of the services involved in the composition as well as the semantic similarity between them are considered as evaluation criteria. The hybrid selection algorithm has been evaluated on a set of scenarios from the trip planning domain and comparatively analyzed with a tabu search-based selection algorithm.

Towards automated web service composition with fluent calculus and domain ontologies

Web service composition is mandatory when complex functional requirements cannot be satisfied by a single Web service. Due to the exponential growth of published Web services, the automatic Web service discovery and composition are highly desirable tasks. This paper presents a new approach for automatic Web service composition based on the the formalism of fluent calculus and using semantic service descriptions. In our approach, the Web service composition process is viewed as an AI planning problem in the fluent calculus formalism. To semantically describe the Web services, we have used a domain ontology which is then translated into a fluent calculus knowledge base, necessary for the composition planning phase. For verifying the composed services, the Label Transition System Analyzer (LTSA) formalism is used. We also present an experimental prototype for the fluent calculus based Web service composition and demonstrate its effectiveness with the help of an application scenario from the social event planning domain.

Selecting the optimal web service composition based on a multi-criteria bee-inspired method

In this paper we present a bee-inspired method for selecting the optimal composition solution. The proposed method uses a composition graph model and a matrix of semantic links to search for the optimal composition solution. For improving the performance of the traditional bee colony optimization algorithm a 1-OPT heuristic is defined. This makes the composition solutions more diverse so as to avoid the stagnation on local optimal solutions. The optimal composition solution is identified by using a multi-criteria fitness function. The fitness function evaluates a composition solution according to QoS attributes and the semantic quality between the services involved in a composition solution.

Semantic Web Service Composition Method Based on Fluent Calculus

This paper presents a new approach for automatic Web service composition based on the formalism of Fluent Calculus using semantic Web service descriptions. In our approach, the Web service composition process is viewed as an AI planning problem in the Fluent Calculus formalism. To semantically describe Web services, we have used a Web service domain ontology which is then translated into a Fluent Calculus knowledge base, necessary for the composition planning phase. For verifying the composed services, the Label Transition System Analyzer (LTSA) formalism is used. The paper also presents an experimental prototype for the Fluent Calculus based Web service composition and demonstrates its effectiveness with the help of an application scenario from the social event planning domain.