Web Service Composition (WSC) can be defined as the problem of consolidating the services regarding the complex user requirements. These requirements can be represented as a workflow. This workflow consists of a set of abstract task sequence where each sub-task represents a definition of some user requirements. In this work, we propose a more efficient neighboring selection process and multi-pheromone distribution method named Enhanced Flying Ant Colony Optimization (EFACO) to solve this problem. The WSC problem has a challenging issue, where the optimization algorithms search the best combination of web services to achieve the functionality of the workflow’s tasks. We aim to improve the computation complexity of the Flying Ant Colony Optimization (FACO) algorithm by introducing three different enhancements. We analyze the performance of EFACO against six of existing algorithms and present a summary of our conclusions.

An Enhanced Ant Colony Optimization Based Algorithm to Solve QoS-Aware Web Service Composition

Web and information grow in size and diversity. Likewise, Web services become difficult to be located or discovered regarding the huge number of the Web services exists today. Thus, the end user may face problem to find suitable Web services that meet his request. Usually, a skilled user or developer is required in order to discover and compose Web services. Increasingly, there is a need to automate Web Services aspects such as discovery and composition in such a way that enhance the interaction between services and the potential user. The proposed study aims to investigate the efficiency of using various type of Swarm Intelligent (SI) algorithms with somatic web technology in the Web services composition and also aims to investigate how can improve the overall composition process by applying an effective Web services discovering strategy based on semantic Web technology; on order to reduce the search space of candidate Web services.

Ant Colony System

In today’s Web, Web Services (WSs) are created and updated on the fly Nowadays, for answering complex needs of users, the construction of new web services based on existing ones is required. It has received a great attention from different communities. This problem is known as web services composition. However, it is one of big challenge problems of recent years in a distributed and dynamic environment. Web services can be composed manually but it is a time consuming task. The automatic web service composition is one of the key features for future the semantic web. The various approaches in field of web service compositions proposed by the researchers. In this paper, we propose a novel architecture for semantic web service composition using clustering and Ant colony algorithm.

An Optimized Semantic Web Service Composition Method Based on Clustering and Ant Colony Algorithm

Web Services Composition Methods and Techniques: A Review

Web Service Composition (WSC) provides a flexible framework for integrating independent web services to satisfy complex user requirements. WSC aims to choose the best web service from a set of candidates. The candidates have the same functionality and different non-functional criteria such as Quality of Service (QoS). In this work, the authors propose an ant-inspired algorithm for such problem. They named it Flying Ant Colony Optimization (FACO). Flying ants inject pheromone not only on the nodes on their paths but also on neighboring nodes increasing their chances of being explored in future iterations. The amount of pheromone deposited on these neighboring nodes is inversely proportional to the distance between them and the nodes on the path. The authors believe that by depositing pheromone on neighboring nodes, FACO may consider a more diverse population of solutions, which may avoid stagnation. The empirical experiments show that FACO outperform Ant Colony Optimization (ACO) for the WSC problem, in terms of the quality of solutions but it requires slightly more execution time.

An Adapted Ant-Inspired Algorithm for Enhancing Web Service Composition

Automatic composition of semantic Web services by requests is one of difficult problems in the field of Web services. In this paper we investigate Web services ontology and ant colony (AC) algorithm and propose a method of composition of semantic Web services (ACAC) that is based on ant colony algorithm. We generate a graph of input and output of semantic Web services, using this method, and then the composition of Web services is transformed into finding a satisfying path in the graph. So AC algorithm is used for efficient composition of Web services. Finally, we have tested ACAC with a test set and the results show that the algorithm can successfully compose the semantic Web services and is also able to ensure the quality and efficiency of composition.

An optimization ant colony algorithm for composition of semantic Web services

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An optimization ant colony algorithm for composition of semantic Web services