Towards personalised and adaptive QoS assessments via context awareness

Lina Barakat; Phillip Taylor; Nathan Griffiths; Adel Taweel; Michael Luck; Simon Miles

doi:10.1111/coin.12129

Towards personalised and adaptive QoS assessments via context awareness

Lina Barakat, Phillip Taylor, Nathan Griffiths, Adel Taweel, Michael Luck, Simon Miles

University of Warwick

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Abstract

Quality of Service (QoS ) properties play an important role in distinguishing between functionally-equivalent services and accommodating the different expectations of users. However, the subjective nature of some properties and the dynamic and unreliable nature of service environments may result in cases where the quality values advertised by the service provider are either missing or untrustworthy. To tackle this, a number of QoS estimation approaches have been proposed, utilising the observation history available on a service to predict its performance. Although the context underlying such previous observations (and corresponding to both user and service related factors) could provide an important source of information for the QoS estimation process, it has only been utilised to a limited extent by existing approaches. In response, we propose a context-aware quality learning model, realised via a learning-enabled service agent, exploiting the contextual characteristics of the domain in order to provide more personalised, accurate and relevant quality estimations for the situation at hand. The experiments conducted demonstrate the effectiveness of the proposed approach, showing promising results (in terms of prediction accuracy) in different types of changing service environments.

Original language	English
Pages (from-to)	468-494
Journal	COMPUTATIONAL INTELLIGENCE
Volume	34
Issue number	2
Early online date	1 Aug 2017
DOIs	https://doi.org/10.1111/coin.12129
Publication status	Published - May 2018

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10.1111/coin.12129

Towards Personalised and Adaptive_BARAKAT_Acc12Apr2017Publishedonline1August2017_GREEN AAM
This is the peer reviewed version of the following article: Barakat et al., in Computational Intelligence (Wiley, 2017) which has been published in final form at 10.1111/coin.12129. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.
Accepted author manuscript, 1.79 MBLicence: Other

Cite this

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Towards personalised and adaptive QoS assessments via context awareness

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