IEEE Access (Jan 2017)

QoS Recommendation in Cloud Services

  • Xianrong Zheng,
  • Li Da Xu,
  • Sheng Chai

DOI
https://doi.org/10.1109/ACCESS.2017.2695657
Journal volume & issue
Vol. 5
pp. 5171 – 5177

Abstract

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As cloud computing becomes increasingly popular, cloud providers compete to offer the same or similar services over the Internet. Quality of service (QoS), which describes how well a service is performed, is an important differentiator among functionally equivalent services. It can help a firm to satisfy and win its customers. As a result, how to assist cloud providers to promote their services and cloud consumers to identify services that meet their QoS requirements becomes an important problem. In this paper, we argue for QoS-based cloud service recommendation, and propose a collaborative filtering approach using the Spearman coefficient to recommend cloud services. The approach is used to predict both QoS ratings and rankings for cloud services. To evaluate the effectiveness of the approach, we conduct extensive simulations. Results show that the approach can achieve more reliable rankings, yet less accurate ratings, than a collaborative filtering approach using the Pearson coefficient.

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