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Sensors 2017, 17(5), 974; doi:10.3390/s17050974

Time-Aware Service Ranking Prediction in the Internet of Things Environment

State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876, China
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Academic Editor: Yuh-Shyan Chen
Received: 28 March 2017 / Revised: 20 April 2017 / Accepted: 25 April 2017 / Published: 27 April 2017
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Abstract

With the rapid development of the Internet of things (IoT), building IoT systems with high quality of service (QoS) has become an urgent requirement in both academia and industry. During the procedures of building IoT systems, QoS-aware service selection is an important concern, which requires the ranking of a set of functionally similar services according to their QoS values. In reality, however, it is quite expensive and even impractical to evaluate all geographically-dispersed IoT services at a single client to obtain such a ranking. Nevertheless, distributed measurement and ranking aggregation have to deal with the high dynamics of QoS values and the inconsistency of partial rankings. To address these challenges, we propose a time-aware service ranking prediction approach named TSRPred for obtaining the global ranking from the collection of partial rankings. Specifically, a pairwise comparison model is constructed to describe the relationships between different services, where the partial rankings are obtained by time series forecasting on QoS values. The comparisons of IoT services are formulated by random walks, and thus, the global ranking can be obtained by sorting the steady-state probabilities of the underlying Markov chain. Finally, the efficacy of TSRPred is validated by simulation experiments based on large-scale real-world datasets. View Full-Text
Keywords: time series analysis; quality of service (QoS); service ranking prediction; Internet of things (IoT) time series analysis; quality of service (QoS); service ranking prediction; Internet of things (IoT)
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Huang, Y.; Huang, J.; Cheng, B.; He, S.; Chen, J. Time-Aware Service Ranking Prediction in the Internet of Things Environment. Sensors 2017, 17, 974.

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