Introducing QoS to Electronic Commerce Applications

Bochmann, Gregor von; Kerhervé, Brigitte; Lutfiyya, Hanan; Salem, Mohamed-Vall M.; Ye, Haiwei

doi:10.1007/3-540-45415-2_11

Cited by 20 publications

(11 citation statements)

References 3 publications

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“…Recently, there is a trend in adopting this concept to web services [9]. The basic aim is to identify the QoS attributes [10][11][12] for improving the quality of web services through replication services [10], load distribution [13], and service redirection [14]. To measure the QoS of a web service, attributes like Response Time, Throughput, Availability, Reliability, Cost, and Response Time are considered.…”

Section: Quality Issues In Web Servicesmentioning

confidence: 99%

Classification of Web Services Using Bayesian Network

Mohanty¹,

Ravi²,

Patra³

2012

JSEA

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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.

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Section: Quality Issues In Web Servicesmentioning

confidence: 99%

Classification of Web Services Using Bayesian Network

Mohanty¹,

Ravi²,

Patra³

2012

JSEA

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“…Recently, there is a trend in adopting this concept to web services [24]. The basic aim is to identify the QoS attributes [8,15,20,29] for improving the quality of web services through replication services [8], load distribution [10], and service redirection [3]. To measure the QoS of a web service, attributes like Response Time, Throughput, Availability, Reliability, Cost, and Response Time are considered.…”

Section: Iiquality Issues In Web Servicesmentioning

confidence: 99%

Application of fuzzy multi attribute decision making analysis to rank web services

Mohanty

Ravi

Patra

2010

2010 International Conference on Computer Information Systems and Industrial Management Applications (CISIM)

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In this paper, we employed modified fuzzy multi attribute decision making (FMADM) to rank web services. The modification to the FMADM is that we employed backpropagation trained neural network (BPNN) instead of the analytic hierarchy process (AHP) to determine the weights of the attributes. Thus, the modified FMADM is a hybrid of knowledge-driven and data-driven models. The FMADM 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, which are fuzzy sets and web services as alternatives. In this paper, min operator, compensatory and operator and product operator are used in aggregating the nine attributes while computing final ranks of web services and their ranks are compared. From the experiments, we conclude that min operator and compensatory and operator produced almost identical rankings and comparable to the classification done in literature.

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“…[21], 'The percentage of time a source is accessible based on technical equipment and statistics' [16] or 'The probability a system is up' [20,26]. In this paper, we use the latter definition.…”

Section: Sku Metricsmentioning

confidence: 99%

Becoming responsive to service usage and performance changes by applying service feedback metrics to software maintenance

Schuur

Jansen

Brinkkemper

2008

2008 23rd IEEE/ACM International Conference on Automated Software Engineering - Workshops

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Software vendors are unaware of how their software performs in the field. They do not know what parts of their software are used and appreciated most and have little knowledge about the behavior of the software and its environment. In this paper we present a metrics-based approach that is used by software vendors to create real-time usage reports, based on data gathered by leveraging aspect-oriented programming techniques. This approach enables software vendors to respond quickly to performance and usage changes in their service software, both at specific customers and concerning the service software in general. We show that by using this approach, vendors can make informed decisions with respect to software requirements management and maintenance. The metrics and usage reports are validated by way of a case study at a Dutch software vendor. While validation shows high potential of the approach, a successful implementation will require change management at the software vendor.

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Introducing QoS to Electronic Commerce Applications

Cited by 20 publications

References 3 publications

Classification of Web Services Using Bayesian Network

Classification of Web Services Using Bayesian Network

Application of fuzzy multi attribute decision making analysis to rank web services

Becoming responsive to service usage and performance changes by applying service feedback metrics to software maintenance

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