Quality CloudCrowd: A Crowdsourcing Platform for QoS Assessment of SaaS Services

被引:0
|
作者
Alkalbani, Asma Musabah [1 ]
Hussain, Farookh Khadeer [1 ]
机构
[1] Univ Technol Sydney, Sch Software, Ctr Artificial Intelligence, Ultimo, Australia
关键词
D O I
10.1007/978-3-319-69835-9_22
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The adoption of Software as a Service (SaaS) has grown rapidly since 2010, and the need for Quality of Service (QoS) information is a significant factor in selecting a trustworthy SaaS service. In the existing literature, little attention has been given to providing QoS information with the SaaS service offering. SaaS providers offer a description of the overall QoS and service performance when they make their service offer; however service user satisfaction is a crucial factor in service selection decision-making. Crowd sourcing has grown in popularity over the last few years for performing tasks such as product design and consumer feedback, in particular, attracts the researchers in the field of client feedback on services or products. In this paper, we propose a novel framework for providing missing QoS values to the cloud marketplace called "Quality CloudCrowd". Our proposed framework comprises of several parts; however, the development of the QCC platform for collecting missing QoS values is the core element of this structure and is the focus of this paper.
引用
收藏
页码:235 / 240
页数:6
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