scholarly journals A Quality of Service Broker Based Process Model for Dynamic Web Service Composition

2011 ◽  
Vol 7 (8) ◽  
pp. 1267-1274 ◽  
Author(s):  
Rathore
Author(s):  
W. Du ◽  
H. Fan ◽  
J. Li ◽  
H. Wang

A lot of work has been done on the geospatial service composition to support advanced processing, spatial calculation, and invoking of heterogeneous data. However, the quality of service chain is rarely considered and the process model cannot be reused. A modeldriven way of geospatial web service composition is proposed in this work, the service composition is treated as an optimization problem by <i>GwcsFlow</i> model and dynamic binding mechanism. The case of facility location analysis is provided to demonstrate the improvements in geospatial service composition through optimization algorithms.


Author(s):  
Bassam Al Shargabi ◽  
Osama Al-haj Hassan ◽  
Alia Sabri ◽  
Asim El Sheikh

Software is gradually becoming more built by composing web services to support enterprise applications integration; thus, making the process of composing web services a significant topic. The Quality of Service (QoS) in web service composition plays a crucial role. As such, it is important to guarantee, monitor, and enforce QoS and ability to handle failures during execution. Therefore, an urgent need exists for a dynamic Web Service Composition and Execution (WSCE) framework based on QoS constraints. A WSCE broker is designed to maintain the following function: intelligent web service selection decisions based on local QoS for individual web service or global QoS based selection for composed web services, execution tracking, and adaptation. A QoS certifier controlled by the UDDI registry is proposed to verify the claimed QoS attributes. The authors evaluate the composition plan along with performance time analysis.


2017 ◽  
Vol 13 (4) ◽  
pp. 181-197 ◽  
Author(s):  
Fadl Dahan ◽  
Khalil El Hindi ◽  
Ahmed Ghoneim

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.


Author(s):  
Bassam Al Shargabi ◽  
Osama Al-haj Hassan ◽  
Alia Sabri ◽  
Asim El Sheikh

Software is gradually becoming more built by composing web services to support enterprise applications integration; thus, making the process of composing web services a significant topic. The Quality of Service (QoS) in web service composition plays a crucial role. As such, it is important to guarantee, monitor, and enforce QoS and ability to handle failures during execution. Therefore, an urgent need exists for a dynamic Web Service Composition and Execution (WSCE) framework based on QoS constraints. A WSCE broker is designed to maintain the following function: intelligent web service selection decisions based on local QoS for individual web service or global QoS based selection for composed web services, execution tracking, and adaptation. A QoS certifier controlled by the UDDI registry is proposed to verify the claimed QoS attributes. The authors evaluate the composition plan along with performance time analysis.


Author(s):  
Adenike Osofisan ◽  
Idongesit E. Eteng ◽  
Iwara Arikpo ◽  
Abel Usoro

The emergence of the Service Oriented computing paradigm with its implicit inclusion of web services has caused a precipitous revolution in software engineering, e-service compositions, and optimization of e-services. Web service composition requests are usually combined with end-to-end Quality of Service (QoS) requirements, which are specified in terms of non-functional properties e.g. response time, throughput, and price. This chapter describes what web services are; not just to the web but to the end users. The state of the art approaches for composing web services are briefly described and a novel game theoretic approach using genetic programming for composing web services in order to optimize service performance, bearing in mind the Quality of Service (QoS) of these web services, is presented. The implication of this approach to cloud computing and economic development of developing economies is discussed.


Web Services ◽  
2019 ◽  
pp. 904-921
Author(s):  
Fadl Dahan ◽  
Khalil El Hindi ◽  
Ahmed Ghoneim

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.


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