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http://dx.doi.org/10.5626/JCSE.2017.11.3.100

Response Time Prediction of IoT Service Based on Time Similarity  

Yang, Huaizhou (School of Computer Science, Xi'an Shiyou University)
Zhang, Li (School of Computer Science, Xi'an Shiyou University)
Publication Information
Journal of Computing Science and Engineering / v.11, no.3, 2017 , pp. 100-108 More about this Journal
Abstract
In the field of Internet of Things (IoT), smarter embedded devices offer functions via web services. The Quality-of-Service (QoS) prediction is a key measure that guarantees successful IoT service applications. In this study, a collaborative filtering method is presented for predicting response time of IoT service due to time-awareness characteristics of IoT. First, a calculation method of service response time similarity between different users is proposed. Then, to improve prediction accuracy, initial similarity values are adjusted and similar neighbors are selected by a similarity threshold. Finally, via a densified user-item matrix, service response time is predicted by collaborative filtering for current active users. The presented method is validated by experiments on a real web service QoS dataset. Experimental results indicate that better prediction accuracy can be achieved with the presented method.
Keywords
Internet of Things; Web service; QoS prediction; Collaborative filtering;
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1 B. Cheng, D. Zhu, S. Zhao, and J. L. Chen, "Situation-aware IoT service coordination using the event-driven SOA paradigm," IEEE Transactions on Network and Service Management, vol. 13, no. 2, pp. 349-361, 2016.   DOI
2 F. Wang, L. Hu, J. Zhou, and K. Zhao, "A data processing middleware based on SOA for the internet of things," Journal of Sensors, vol. 2015, no. 4, pp. 1-8, 2015.
3 J. Li, X. Luo, Y. N. Xia, Y. K. Han, and Q. S. Zhu, "A time series and reduction-based model for modeling and QoS prediction of service compositions," Concurrency and Computation: Practice and Experience, vol. 27, no. 1, pp. 146-163, 2014.   DOI
4 Y. Ngoko, C. Cerin, and A. Goldman, "Graph reuction for QoS prediction of cloud-service compositions," Business Process Integration and Management, vol. 7, no. 2, pp. 89-102, 2014.   DOI
5 V.V. Atluri, and H. Mohanty, "Web service response time prediction using HMM and bayesian network," in Proceedings of the International Conference on Intelligent Computing, Communication and Devices, Bhubaneswar, India, 2014, pp. 327-335.
6 D. J. Yu, Y. Liu, Y. S. Xu, and Y. Yin, "Personalized QoS prediction for web services using latent factor models," in Proceedings of the 2014 IEEE International Conference on Services Computing, Anchorage, AK, 2014, pp. 107-114.
7 Z. Chen, L.M. Shen, and F. Li, "Exploiting web service geographical neighborhood for collaborative QoS prediction," Future Generation Computer Systems, vol. 68, no. 3, pp. 248- 259, 2017.   DOI
8 V. Narayan, R. K. Mehta, M. Rai, A. Gupta, M. Singh, S. Verma, A. Patel, and S. Yadav, "E-Commerce recommendation method based on collaborative filtering technology," International Journal of Current Engineering and Technology, vol. 7, no. 3, pp. 974-982, 2017.
9 Z. B. Zheng, and M. R. Lyu, "Collaborative reliability prediction for service-oriented systems," in Proceedings of the ACM/IEEE 32nd International Conference on Software Engineering, Cape Town, South Africa, 2010, pp. 35-44.
10 Z. B. Zheng, H. Ma, M. R. Lyu, and I. King, "QoS-aware web service recommendation by collaborative filtering," IEEE Transactions on Services Computing, vol. 4, no. 2, pp. 140-152, 2011.   DOI
11 W. Lo, J. W. Yin, Y. Li, and Z. H. Wu, "Efficient web service QoS prediction using local neighborhood matrix factorization," Engineering Applications of Artificial Intelligence, vol. 38, pp. 14-23, 2015.   DOI
12 Z. B. Zheng, H. Ma, M. R. Lyu, and I. King, "Collaborative web service QoS prediction via neighborhood integrated matrix factorization," IEEE Transactions on Services Computing, vol. 6, no. 3, pp. 289-299, 2013.   DOI
13 M. Munoz-Organero, G.A. Ramirez-Gonzalez, P. J. Munoz-Merino, and C. D. Kloos, "Recommender system based on space-time similarities," IEEE Pervasive Computing, vol. 9, no. 3, pp. 81-87, 2010.   DOI
14 M. Chen, J. F. Wan, and F. Li, "Machine-to-machine communications: architectures, standards and applications," KSII Transactions on Internet and Information Systems, vol. 6, no. 2, pp. 480-497, 2012.   DOI
15 S. N. Han, G. M. Lee, N. Crespi, V. L. Nguyen, H. Kyoungwoo, B. Mihaela, and G. Patrick, "DPWSim: a devices profile for web services (DPWS) simulator," IEEE Internet of Things Journal, vol. 2, no. 3, pp. 221-229, 2015.   DOI
16 F. Giancarlo, "Agents meet the IoT: toward ecosystems of networked smart objects," IEEE Systems, Man, and Cybernetics Magazine, vol. 2, no. 2, pp. 43-47, 2016.   DOI