Investigating web services on the world wide web

Al‐Masri, Eyhab; Mahmoud, Qusay H.

doi:10.1145/1367497.1367605

Cited by 479 publications

(185 citation statements)

References 23 publications

Supporting

Mentioning

181

Contrasting

Unclassified

Order By: Relevance

“…In literature different data sets are available for research on QoS (e.g., [2], [21]). However, these data sets do not contain information about the operations invoked but only the services names and their url.…”

Section: Discussionmentioning

confidence: 99%

A Genetic Algorithm to Find the Adequate Granularity for Service Interfaces

Romano

Pinzger

2014

2014 IEEE World Congress on Services

View full text Add to dashboard Cite

Abstract-The relevance of the service interfaces' granularity and its architectural impact have been widely investigated in literature. Existing studies show that the granularity of a service interface, in terms of exposed operations, should reflect their clients' usage. This idea has been formalized in the Consumer-Driven Contracts pattern (CDC). However, to the best of our knowledge, no studies propose techniques to assist providers in finding the right granularity and in easing the adoption of the CDC pattern.In this paper, we propose a genetic algorithm that mines the clients' usage and suggests Façade services whose granularity reflect the usage of each different type of clients. These services can be deployed on top of the original service and they become contracts for the different types of clients satisfying the CDC pattern. A first study shows that the genetic algorithm is capable of finding Façade services and it outperforms a random search approach.

show abstract

Section: Discussionmentioning

confidence: 99%

A Genetic Algorithm to Find the Adequate Granularity for Service Interfaces

Romano

Pinzger

2014

2014 IEEE World Congress on Services

View full text Add to dashboard Cite

show abstract

“…The most comprehensive data sets for web-services classification used by [19], [31], [32], include ten crisp independent attributes and one linguistic expression which represents the trust level of the web-service. To the best of our knowledge, in all studies in the literature, the trust terms (being platinum, gold, silver and bronze) are quantized to 1 to 4, respectively.…”

Section: Methodsmentioning

confidence: 99%

The prediction of trust rating based on the quality of services using fuzzy linear regression

Mashinchi

Orgun

et al. 2011

2011 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2011)

View full text Add to dashboard Cite

Abstract-With the advent of service-oriented computing, the issue of trust and Quality of Service (QoS) have become increasingly important. In service-oriented environments, when there are a few service providers providing the same service, a service client would be keen to know the trustworthiness of each service provider in the forthcoming transaction. The trust value of a delivered service from a service provider can be predicted according to a set of advertised QoS data collected by the trust management authority. Although trust and QoS are qualitative by nature, most data sets represent trust and QoS in the ordinal form for the sake of simplicity.This paper introduces a new approach based on Fuzzy Linear Regression Analysis (FLRA) to extract qualitative information from quantitative data and so use the obtained qualitative information for better modeling of the data. For verification purposes, the proposed approach can be applied for the trust prediction in the forthcoming transaction based on a set of advertised QoS in service-oriented environments.

show abstract

“…A Bayesian network is a directed acyclic graph model that represents conditional independencies between a set of variables [18,19]. It has two constituents: One is a network graphical structure which is a directed acyclic graph with the nodes of variables and arcs of relations.…”

Section: Overview Of Bayesian Networkmentioning

confidence: 99%

Classification of Web Services Using Bayesian Network

Mohanty¹,

Ravi²,

Patra³

2012

JSEA

View full text Add to dashboard Cite

In this paper, we employed Naïve Bayes, Markov blanket and Tabu search to rank web services. The Bayesian Network is demonstrated on a dataset taken from literature. The dataset consists of 364 web services whose quality is described by 9 attributes. Here, the attributes are treated as criteria, to classify web services. From the experiments, we conclude that Naïve based Bayesian network performs better than other two techniques comparable to the classification done in literature.

show abstract

Investigating web services on the world wide web

Cited by 479 publications

References 23 publications

A Genetic Algorithm to Find the Adequate Granularity for Service Interfaces

A Genetic Algorithm to Find the Adequate Granularity for Service Interfaces

The prediction of trust rating based on the quality of services using fuzzy linear regression

Classification of Web Services Using Bayesian Network

Contact Info

Product

Resources

About