Identifying Optimal Composite Services by Decomposing the Service Composition Problem

2011 ◽  
Author(s):  
Zachary J. Oster ◽  
Ganesh Ram Santhanam ◽  
Samik Basu
Keyword(s):  
Service Composition ◽  
Composition Problem ◽  
Composite Services

Achieving Dependable Composite Services through Two-Level Redundancy

2012 ◽  
pp. 295-316
Author(s):  
Hailong Sun ◽  
Jin Zeng ◽  
Huipeng Guo ◽  
Xudong Liu ◽  
Jinpeng Huai
Keyword(s):  
Business Process ◽  
Service Composition ◽  
Service Performance ◽  
Structural Redundancy ◽  
Composite Service ◽  
Service Oriented ◽  
Composite Services ◽  
Insightful Analysis ◽  
Process Level

Service composition is a widely accepted method to build service-oriented applications. However, due to the uncertainty of infrastructure environments, service performance and user requests, service composition faces a great challenge to guarantee the dependability of the corresponding composite services. In this chapter, we provide an insightful analysis of the dependability issue of composite services. And we present a solution based on two-level redundancy: component service redundancy and structural redundancy. With component service redundancy, we study how to determine the number of backup services and how to guarantee consistent dependability of a composite service. In addition, structural redundancy aims at further improving dependability at business process level through setting up backup execution paths.

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.

DYNAMIC SERVICE COMPOSITION: A DISCOVERY-BASED APPROACH

2008 ◽  
Vol 18 (02) ◽  
pp. 199-222 ◽  
Author(s):  
JONATHAN LEE ◽  
SHANG-PIN MA ◽  
YING-YAN LIN ◽  
SHIN-JIE LEE ◽  
YAO-CHIANG WANG
Keyword(s):  
Service Composition ◽  
Service Discovery ◽  
Main Trend ◽  
Service Availability ◽  
Composite Service ◽  
Composite Pattern ◽  
Contract Net ◽  
Dynamic Service Composition ◽  
Service Oriented ◽  
Composite Services

Service-Orientated Computing (SOC) has become a main trend in software engineering that promotes the construction of applications based on the notion of services. SOC has recently attracted the researchers' attention and has been adopted industry-wide. However, service composition that enables one to aggregate existing services into a new composite service is still a highly complex and critical task in service-oriented technology. To enhance availability of composite services, we propose a discovery-based service composition framework to better integrate component services in both static and dynamic manner, including (1) to devise a notion of service availability especially for composition; (2) to develop a dynamic service composition (DSC) pattern for addressing the issues of service availability; and (3) to extend Contract Net Protocol (ECNP) to coordinate service discovery, composition and invocation based on the composite pattern. The main benefit of the proposed approach is better availability through attaching multiple candidate services for future binding.

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.

scholarly journals Comprehensive Quality-Aware Automated Semantic Web Service Composition

2021 ◽  
Author(s):  
◽  
Chen Wang
Keyword(s):  
Web Service ◽  
Service Composition ◽  
State Of The Art ◽  
Web Service Composition ◽  
Design Stage ◽  
Nsga Ii ◽  
Multi Objective ◽  
Art Works ◽  
Composite Services ◽  
Effectiveness And Efficiency

<p>Automated web service composition is one of the ultimate goals of service-oriented computing. It loosely couples web services to accommodate users' complex requirements. Evolutionary Computation (EC) techniques combined with AI planning have been successfully proposed to efficiently produce composite services with near-optimal Quality of Semantic Matchmaking (QoSM) and/or Quality of Service (QoS), which measure the satisfaction of the functional and non-functional requirements from users, respectively. Despite some recent progress, both the effectiveness and efficiency of existing approaches need further improvement to enhance the competitive advantage of service providers. The overall goal of this thesis is to propose novel EC-based fully automated service composition approaches that can effectively and efficiently solve challenging single-objective, multi-objective, and dynamic service composition problems.  Firstly, this thesis proposes two novel Estimation of Distribution Algorithm (EDA) based approaches (called EDA-NHM and EDA-EHM) and one memetic EDA-based approach with four different local search operators to single-objective fully automated web service composition that jointly optimizes QoSM and QoS. EDA-NHM and EDA-EHM are proposed with novel permutation-based and DAG-based representations to model the distribution of composition solutions with respect to varied service composition workflows. Two sampling techniques are also studied in EDA-NHM and EDA-EHM to effectively and efficiently sample new promising permutations and functionally valid DAGs, respectively. These two EDA-based approaches are compared to state-of-the-art works. The comparisons reveal that EDA-NHM produces better-quality composite services than EDA-EHM and the state-of-the-art works. On the other hand, EDA-EHM achieves the highest efficiency among all the competing EC-based methods, delivering moderate effectiveness. Furthermore, one proposed memetic approaches built upon EDA-NHM (called MEEDA-LOP) pushes the cutting-edge performance in terms of effectiveness and efficiency.   Secondly, this thesis studies two categories of multi-objective service composition problems: one category aims to generate a set of approximated Pareto optimal solutions for users to choose from, while the other category aims to generate multiple composite services for multiple user segments with distinctive preferences on QoSM. To effectively and efficiently handle the first category of problems, a memetic approach based on Non-dominated Sorting Genetic Algorithm II (NSGA-II), called MNSGA2-EDA, is proposed by enhancing NSGA-II with EDA-based local search. The novelty of this method lies in the innovative use of EDA for effective and efficient local improvements, rather than for global exploration. MNSGA2-EDA is compared to state-of-the-art multi-objective works, for studying its performance. We found that MNSGA2-EDA achieves much higher effectiveness and efficiency in finding Pareto optimal solutions. The second category of problems can be naturally treated as multitasking problems. Two novel multi-factorial evolutionary algorithms (called PMFEA and PMFEA-EDA) are proposed to effectively and efficiently solve this category of problems. These two algorithms implicitly or explicitly learn and share the knowledge of good solutions evolved so far for different tasks. We compare PMFEA and PMFEA-EDA with state-of-the-art works. We found that both PMFEA-EDA and PMFEA are performed at the cost of only a fraction of time compared to the single-tasking state-of-the-art works, which solve one task at a time. We also found that PMFEA-EDA yields solutions with the highest quality, confirming that learning and sharing knowledge explicitly is superior to learning and sharing knowledge implicitly.   Thirdly, this thesis studies a new dynamic service composition problem, focusing on handling stochastic service failures. We effectively handle this problem via two stages --- the design stage and the execution stage. Particularly, two accurate robustness measures are proposed based on Monte Carlo sampling and a lower bound estimation, respectively. These robustness measures are utilized in two proposed GA-based approaches (called GA-MC and GA-RE) at the design stage, to generate baseline composite solutions with high robustness. These baseline solutions can cope with the stochastic service failures robustly via a repairing process that supports continued high-quality execution of a composite service at the execution stage. Meanwhile, we propose a GA-2Stage algorithm by introducing a new adaptive evolutionary control mechanism, which supports two sequential evolutionary stages with two different fitness evaluation methods. These approaches are compared to each other to determine the most suitable method. Our experimental comparisons reveal that GA-RE algorithm with lower bound estimation outperforms GA-MC algorithm with Monte Carlo sampling estimation in finding composition solutions with high robustness, regardless of the size of the service repositories. Besides, compared to GA-RE, GA-2Stage achieves the highest efficiency with a negligible impact on the effectiveness at the execution stage, regardless of the service repositories' size.</p>

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.

Sign in / Sign up

Export Citation Format

Share Document