An Efficient Web Service Composition Approach Based on improved Particle Swarm Optimization Model

Author(s):  
Yi Liang ◽  
YingYuan Xiao
2021 ◽  
Vol 9 (2) ◽  
pp. 65-70
Author(s):  
Laishram Jenny Chanu ◽  
◽  
Arnab Paul ◽  

Lots of Web Services are available which differ in their QoS values but can perform a similar task. Discovery mechanism selects the best Web Service according to their QoS values and functional attributes. Cases arise, where the discovery mechanism fails, as a user’s complex query cannot be satisfied by a single Web Service. This can be solved by Web Service composition where multiple Web Services are combined to give a composite Web Service which meet user’s complex query. Our work is mainly focused on composition of Web Services that efficiently meets the user’s query. Different algorithms have been discussed and used by different researchers in this field. One of the most blooming topics is the use of evolutionary algorithms in optimization problems. In our work, we have chosen Particle Swarm Optimization Algorithm approach to discover the best efficient composition. Then, Weight Improved Particle Swarm Optimization Algorithm is used to improve the results which were found to be quite satisfying and efficient.


2019 ◽  
Vol 16 (1) ◽  
pp. 1-21 ◽  
Author(s):  
Hela Fekih ◽  
Sabri Mtibaa ◽  
Sadok Bouamama

Generally, the composition is the process of combining services to fulfill complex tasks based on their functional and non-functional values such as quality of services (QoS) and context attributes. However, to produce a composition with values that satisfy many requirements is a challenging focus. In this article, the authors proposed a new approach centered evolutionary algorithm called the harmony particle swarm optimization (HPSO) algorithm that leads to an efficient composition with better performance and execution time. The authors' proposed method is a new hybrid version of the harmony search and the particle swarm optimization. The HPSO is designed to generate the best web service composition in a discrete search space. Furthermore, the method includes two filtering processes called Skyline operator and local consistency reinforcement techniques. These methods filter the search space and keep only the most representative candidate services. Results show the effectiveness and the accuracy of the proposed approach.


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