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A Study on the Effect of Application and Resource Characteristics on the QoS in Service Provisioning Environments

A Study on the Effect of Application and Resource Characteristics on the QoS in Service Provisioning Environments

Theodora Varvarigou, Konstantinos Tserpes, Dimosthenis Kyriazis, Fabrizio Silvestri, Nikolaos Psimogiannos
Copyright: © 2010 |Volume: 1 |Issue: 1 |Pages: 21
ISSN: 1947-3532|EISSN: 1947-3540|ISSN: 1947-3532|EISBN13: 9781616929763|EISSN: 1947-3540|DOI: 10.4018/jdst.2010090804
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MLA

Varvarigou, Theodora, et al. "A Study on the Effect of Application and Resource Characteristics on the QoS in Service Provisioning Environments." IJDST vol.1, no.1 2010: pp.55-75. http://doi.org/10.4018/jdst.2010090804

APA

Varvarigou, T., Tserpes, K., Kyriazis, D., Silvestri, F., & Psimogiannos, N. (2010). A Study on the Effect of Application and Resource Characteristics on the QoS in Service Provisioning Environments. International Journal of Distributed Systems and Technologies (IJDST), 1(1), 55-75. http://doi.org/10.4018/jdst.2010090804

Chicago

Varvarigou, Theodora, et al. "A Study on the Effect of Application and Resource Characteristics on the QoS in Service Provisioning Environments," International Journal of Distributed Systems and Technologies (IJDST) 1, no.1: 55-75. http://doi.org/10.4018/jdst.2010090804

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Abstract

This article deals with the problem of quality provisioning in business service-oriented environments, examining the resource selection process as an initial matching of the provided to the demanded QoS. It investigates how the application and resource characteristics affect the provided level of QoS, a relationship that intuitively exists but has not yet being mapped. To do so, it focuses on identifying the application and resource parameters that affect the customer-defined QoS parameters. The article realistically centres upon modeling a data mining application and simple PC nodes in order to study how they affect response times. It moves on, by proving the existence of these specific relations and maps them using simple artificial neural networks so as to be able to wrap them in a single mechanism for resource selection based on customer QoS requirements and real time provider QoS capabilities.

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