Bi-objective web service composition problem in multi-cloud environment: a bi-objective time-varying particle swarm optimisation algorithm

Author(s):  
Mirsaeid Hosseini Shirvani
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.


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