How to select dynamically a QoS-driven composite web service by a multi-agent system using CBR method

Siala, Fatma; Ghédira, Khaled

doi:10.1504/ijwmc.2014.063054

Cited by 5 publications

(5 citation statements)

References 29 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Other research studies consider a QoS‐aware service composition as a multiobjective optimization problem. One approach is to perform an exhaustive search and emulate all the possible compositions . This can guarantee finding an optimal composition, but it suffers from combinatorial explosion and is inefficient.…”

Section: Related Workmentioning

confidence: 99%

“…Other population‐based approaches, such as service domain–oriented artificial bee colony and ant colony optimization, only provide near‐optimal solutions. As for agent‐based solutions,() they are always associated with scalability issues and suffer from distribution and performance problems. The performance issues and high execution time are common problems in graph‐based solutions as in the work of da Silva et al The integer linear programming approach deals with a set of constraints when treating an objective function.…”

Section: Related Workmentioning

confidence: 99%

“…Regarding selection criteria, most approaches have addressed the general aspect of QoS. Some works have focused on specific QoS attributes such as response time in the works of Ahmed et al and Rezaie et al, trust in the work of Yu et al, and price in the work of Rezaie et al Very few works have negotiated QoS and SLA when dealing with service selection, such as those by Ardagna and Pernici, Sun et al, and Siala and Ghedira …”

Section: Related Workmentioning

confidence: 99%

See 2 more Smart Citations

A negotiation‐based service selection approach using swarm intelligence and kernel density estimation

Mezni

Sellami

2018

Softw Pract Exp

View full text Add to dashboard Cite

Nowadays, the cloud computing environment is becoming a natural choice to deploy and provide Web services that meet user needs. However, many services provide the same functionality and high quality of service (QoS) but different self-adaptive behaviors. In this case, providers' adaptation policies are useful to select services with high QoS and high quality of adaptation (QoA). Existing approaches do not take into account providers' adaptation policies in order to select services with high reputation and high reaction to changes, which is important for the composition of self-adaptive Web services. In order to actively participate to compositions, candidate services must negotiate their self-* capabilities. Moreover, they must evaluate the participation constraints against their capabilities specified in terms of QoS and adaptation policies. This paper exploits a variant of particle swarm optimization and kernel density estimation in the selection of service compositions and the concurrent negotiations of their QoS and QoA capabilities. Selection and negotiation processes are held between intelligent agents, which adopt swarm intelligence techniques for achieving optimal selection and optimal agreement on providers' offers.To resolve unknown autonomic behavior of candidate services, we deal with the lack of such information by predicting the real QoA capabilities of a service through the kernel density estimation technique. Experiments show that our solution is efficient in comparison with several state-of-the-art selection approaches. KEYWORDSkernel density estimation, negotiation, particle swarm optimization, self-* Web service, service selection Over the last decade, service-oriented computing has emerged as a prominent computing paradigm and changed the way software applications are modeled, provisioned, and consumed. 1 Moreover, service-oriented computing has a reciprocal relationship with cloud computing, as one provides the computing of services and the other provides the services of computing. 2 Indeed, the prevalence of cloud computing as a new model for enabling on-demand access to a shared pool of configurable computing resources has encouraged several companies like Microsoft, Amazon, Salesforce, and Google to publish their cloud platforms in order to provide computing resources and cloud data storage centers. This rapid Softw Pract Exper. 2018;48:1285-1311.wileyonlinelibrary.com/journal/spe

show abstract

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

A negotiation‐based service selection approach using swarm intelligence and kernel density estimation

Mezni

Sellami

2018

Softw Pract Exp

View full text Add to dashboard Cite

show abstract

“…A new negotiation protocol was also presented to support coordinated negotiation. A framework was presented to select composite services by a multi-agent system using a case-based reasoning method [26], [27]. The authors of [8] introduced an approach for the Web service selection problem with large scale processes and severe QoS constraints.…”

Section: Related Workmentioning

confidence: 99%

Multi-Phase Ant Colony System for Multi-Party Data-Intensive Service Provision

Wang

Shen

2016

IEEE Trans. Serv. Comput.

View full text Add to dashboard Cite

The rapid proliferation of enormous sources of digital data has led to greater dependence on data-intensive services. Each service may actually request or create a large amount of data sets. To compose these services will be more challenging. Issues such as autonomy, scalability, adaptability, and robustness, become difficult to resolve. In order to automate the process of reaching an agreement among service composers, service providers, and data providers, an ant-inspired negotiation mechanism is considered in this paper. We exploit a group of agents automatically negotiating to establish agreeable service contracts. Twostage negotiation procedures are used in our data-intensive service provision model, which will provide effective and efficient service selection for service composers. We also present a multi-phase, multi-party negotiation protocol, where the ant colony system is applied to select services with the best or near-optimal utility outputs. In order to adapt the ant colony system to handle the dynamic scenarios during negotiations, we also discuss several strategies for modifying the pheromone information in the first place. The experimental results show that our negotiation-based approach can facilitate the data-intensive service provision with better outcome. University of Wollongong, NSW, Australia E-mail: lw840@uowmail.edu.au, jshen@uow.edu.au ! Abstract-The rapid proliferation of enormous sources of digital data has led to greater dependence on data-intensive services. Each service may actually request or create a large amount of data sets. To compose these services will be more challenging. Issues such as autonomy, scalability, adaptability, and robustness, become difficult to resolve. In order to automate the process of reaching an agreement among service composers, service providers, and data providers, an ant-inspired negotiation mechanism is considered in this paper. We exploit a group of agents automatically negotiating to establish agreeable service contracts. Two-stage negotiation procedures are used in our data-intensive service provision model, which will provide effective and efficient service selection for service composers. We also present a multi-phase, multi-party negotiation protocol, where the ant colony system is applied to select services with the best or near-optimal utility outputs. In order to adapt the ant colony system to handle the dynamic scenarios during negotiations, we also discuss several strategies for modifying the pheromone information in the first place. The experimental results show that our negotiation-based approach can facilitate the data-intensive service provision with better outcome.

show abstract

“…More advanced web service composition proposals are based on ontology [2], multi-agent systems [3], genetic algorithms [4], stochastic optimization algorithm [5], linear programming [6], query languages [7], and multicriteria evaluation [8] [9][10] [11] A recent survey of web service composition approaches is available in [12].…”

Section: Introductionmentioning

confidence: 99%

QoS-Enhanced Broker for Composite Web Service Selection

Chakhar¹

2012

2012 Eighth International Conference on Signal Image Technology and Internet Based Systems

View full text Add to dashboard Cite

The paper proposes a layered system for web service composition. The input for the system is the specification of the desired service, including both functional and non-functional requirements. The composition operation takes as input a generic composition graph defined based on the functional requirements. Then, the set of potential compositions is identified based on "hard" non-functional requirements. This set is represented in terms of an extended version of the composition graph that permits to take into account the different BPEL constructors. Finally, best composition(s) are identified by solving a bi-objective shortest path problem on the transformed composition graph.

show abstract

How to select dynamically a QoS-driven composite web service by a multi-agent system using CBR method

Cited by 5 publications

References 29 publications

A negotiation‐based service selection approach using swarm intelligence and kernel density estimation

A negotiation‐based service selection approach using swarm intelligence and kernel density estimation

Multi-Phase Ant Colony System for Multi-Party Data-Intensive Service Provision

QoS-Enhanced Broker for Composite Web Service Selection

Contact Info

Product

Resources

About