Nature inspired meta-heuristic algorithms for solving the service composition problem in the cloud environments

2018 ◽  
Vol 31 (12) ◽  
pp. e3708 ◽  
Author(s):  
Saied Asghari ◽  
Nima Jafari Navimipour
Keyword(s):  
Service Composition ◽  
Heuristic Algorithms ◽  
Composition Problem ◽  
Cloud Environments

Model Maturity-Based Model Service Composition in Cloud Environments

2021 ◽  
pp. 102389
Author(s):  
Ying Liu ◽  
Lin Zhang ◽  
Yongkui Liu ◽  
Yuanjun Laili ◽  
Weicun Zhang
Keyword(s):  
Service Composition ◽  
Cloud Environments

Applying Evolutionary Many-Objective Optimization Algorithms to the Quality-Driven Web Service Composition Problem

2016 ◽  
pp. 170-194
Author(s):  
Arion de Campos Jr. ◽  
Aurora T. R. Pozo ◽  
Silvia R. Vergilio
Keyword(s):  
Web Services ◽  
Web Service ◽  
Service Composition ◽  
Optimization Algorithms ◽  
Web Service Composition ◽  
Nsga Ii ◽  
Preference Relations ◽  
Multi Objective ◽  
Composition Problem

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.

Parameter Tuning for S-ABCPK

2019 ◽  
Vol 16 (2) ◽  
pp. 88-109
Author(s):  
Ruilin Liu ◽  
Zhongjie Wang ◽  
Xiaofei Xu
Keyword(s):  
Service Composition ◽  
Time Complexity ◽  
Parameter Tuning ◽  
Validation Dataset ◽  
Bee Colony ◽  
Composition Problem ◽  
The Neural Network ◽  
Service Oriented ◽  
Optimum Solution ◽  
Priori Knowledge

QoS-aware service composition problem has been drawn great attention in recent years. As an NP-hard problem, high time complexity is inevitable if global optimization algorithms (such as integer programming) are adopted. Researchers applied various evolutionary algorithms to decrease the time complexity by looking for a near-optimum solution. However, each evolutionary algorithm has two or more parameters, the values of which are to be assigned by algorithm designers and likely have impacts on the optimization results (primarily time complexity and optimality). The authors' experiments show that there are some dependencies between the features of a service composition problem, the values of an evolutionary algorithm's parameters, and the optimization results. In this article, the authors propose an improved algorithm called Service-Oriented Artificial Bee Colony algorithm considering Priori Knowledge (S-ABCPK) to solve service composition problem and focus on the S-ABCPK's parameter turning issue. The objective is to identify the potential dependency for designers of a service composition algorithm easily setting up the values of S-ABCPK parameters to obtain a preferable composition solution without many times of tedious attempts. Eight features of the service composition problem and the priori knowledge, five S-ABCPK parameters and two metrics of the final solution are identified. Based on a large volume of experiment data, S-ABCPK parameter tuning for a given service composition problem is conducted using C4.5 algorithm and the dependency between problem features and S-ABCPK parameters are established using the neural network method. An experiment on a validation dataset shows the feasibility of the approach.

Planning Based Service Composition

2011 ◽  
pp. 210-241
Author(s):  
Maja Vukovic ◽  
Peter Robinson
Keyword(s):  
Service Composition ◽  
Future Research ◽  
Planning Problem ◽  
Planning Systems ◽  
Research Directions ◽  
Technical Requirements ◽  
Plan Optimization ◽  
Composition Problem ◽  
Future Research Directions ◽  
Domain Description

This chapter presents how automated service composition can be considered as a planning problem. Furthermore it identifies the following three specific technical requirements for planning systems in order to handle service composition problem: (1) richness of domain description, (2) control constructs for assembling complex actions, and (3) a mechanism for plan optimization. This chapter illustrates a number of existing planning systems and discusses their applicability to automated service composition. The chapter then describes a service composition framework, based on a forward chaining planner, and how the abstract plan is instantiated into an executable service. Finally, the chapter discusses future research directions in planning based service composition.

Web Services

2007 ◽  
pp. 244-267
Author(s):  
Bernd Aman ◽  
Salima Benbernou ◽  
Benjamin Nguyen
Keyword(s):  
Web Services ◽  
Web Service ◽  
Service Composition ◽  
Web Applications ◽  
Loosely Coupled ◽  
Composition Problem ◽  
Service Oriented ◽  
Service Paradigm ◽  
Current Standards ◽  
The Web

Unlike traditional applications, which depend upon a tight interconnection of all program elements, Web service applications are composed of loosely coupled, autonomous and independent services published on the Web. In this chapter, we first introduces the concept of service oriented computing (SOC) on the Web and the current standards enabling the definition and publication of Web services. This technology’s next evolution is to facilitate the creation and maintenance of Web applications. This can be achieved by exploiting the self-descriptive nature of Web services combined with more powerful models and languages for composing Web services. A second objective of this chapter is to illustrate the complexity of the Web service composition problem and to provide a representative overview of the existing approaches. The chapter concludes with a short presentation of two research projects exploiting and extending the Web service paradigm.

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