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A Service-oriented device selection solution based on user satisfaction and device performance in a ubiquitous environment

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Abstract

Ubiquitous computing provides the vision of a smart space filled with various smart devices and services where users can navigate with seamless interaction. To achieve such an intelligent scene, service providers attempt to fulfill the functional requirements of users as well as their non-functional demands, such as user satisfaction. Such non-functional demands depend on required services as well as the devices that execute them. For instance, different devices may provide different user satisfaction for an identical service. Currently, selecting a desired device for a requested service is generally completed manually. However, it is a challenge to match a desired device to a service in the aforementioned smart environment because a service is an abstract concept associated with user intention and experience, whereas a device is a concrete item associated with physical functionalities. Therefore, an automatic mechanism is imperative to balance the benefits and drawbacks of selecting a specific device to instantiate a particular service for a certain consumer. The objective of the current paper is to propose a solution that automatically selects one device among multiple devices with overlapping or identical functionalities for a specific given service to achieve maximum user satisfaction. To achieve this, the device selection procedure in a ubiquitous environment is decomposed into four tasks: 1) filtering to obtain candidate devices that are functionally available for the given service, 2) predicting user satisfaction with these candidate devices considering historic usage, 3) estimating device performance based on available device resources, and 4) selecting the top-ranked device to achieve maximum user satisfaction. This study constructs a quantitative metric for selecting a device for a certain service by quantitating service-oriented device performance based on available device resources and predicting user satisfaction considering historic usage. This method is validated through a comparison to another quantitative solution that considers user preference and a method that simply considers device capabilities. Using an example scenario, the overall hit rate of this proposed method exceeds those of the other two methods, and the experimental results indicate that the proposed method is helpful for automatically selecting a user-desired device for a specific service.

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References

  1. Badr Y, Abraham A, Biennier F, Grosan C (2008) Enhancing web service selection by user preferences of non-functional features. In: Next Generation Web Services Practices, 2008. NWESP'08. 4th International Conference on, 2008. IEEE:60–65.

  2. Brønsted J, Hansen KM, Ingstrup M (2007) A survey of service composition mechanisms in ubiquitous computing. Workshop on Requirements and Solutions for Pervasive Software Infrastructures 2007:87–92

    Google Scholar 

  3. Demers L, Weiss-Lambrou R, Ska B (2002) The Quebec User Evaluation of Satisfaction with Assistive Technology (QUEST 2.0): an overview and recent progress. Technol Disabil 14(3):101–105

    Google Scholar 

  4. Doll WJ, Torkzadeh G (1988) The measurement of end-user computing satisfaction. MIS Q 12(2)

  5. Dumas B, Lalanne D, Oviatt S (2009) Multimodal interfaces: A survey of principles, models and frameworks. In: Human Machine Interaction. Springer:3–26.

  6. Elting C, Zwickel J, Malaka R (2002) Device-dependent modality selection for user-interfaces: an empirical study. In: Proceedings of the 7th international conference on Intelligent user interfaces, 2002. ACM:55–62.

  7. Friday A, Davies N, Wallbank N, Catterall E, Pink S (2004) Supporting service discovery, querying and interaction in ubiquitous computing environments. Wirel Netw 10(6):631–641

    Article  Google Scholar 

  8. Golub GH, Reinsch C (1970) Singular value decomposition and least squares solutions. Numer Math 14(5):403–420

    Article  MathSciNet  MATH  Google Scholar 

  9. Helal S, Desai N, Verma V, Lee C (2003) Konark-a service discovery and delivery protocol for ad-hoc networks. In: Wireless Communications and Networking, 2003. WCNC 2003. 2003 IEEE, (3):2107–2113.

  10. Huhns MN, Singh MP (2005) Service-oriented computing: Key concepts and principles. Internet Computing, IEEE 9(1):75–81

    Article  Google Scholar 

  11. Kaowthumrong K, Lebsack J, Han R (2002) Automated selection of the active device in interactive multi-device smart spaces. In: Workshop at UbiComp 2002(2)

  12. Kim M-K, Park M-C, Jeong D-H (2004) The effects of customer satisfaction and switching barrier on customer loyalty in Korean mobile telecommunication services. Telecommun Policy 28(2):145–159

    Article  Google Scholar 

  13. Klema V, Laub AJ (1980) The singular value decomposition: Its computation and some applications. Automatic Control, IEEE Transactions on 25(2):164–176

    Article  MathSciNet  MATH  Google Scholar 

  14. Lin N, Kuter U, Sirin E (2008) Web service composition with user preferences. In: The Semantic Web: Research and Applications. Springer:29–643.

  15. Mukhtar H, Belaïd D, Bernard G (2009) User preferences-based automatic device selection for multimedia user tasks in pervasive environments. In: Networking and Services, 2009. ICNS'09. Fifth International Conference on, 2009. IEEE:43–48.

  16. Oviatt S (2003) Multimodal interfaces. The human-computer interaction handbook: Fundamentals, evolving technologies and emerging applications:286–304.

  17. Pan G, Xu Y, Wu Z, Li S, Yang LT, Lin M, Liu Z (2011) TaskShadow: toward seamless task migration across smart environments. IEEE Intell Syst 26(3):50–57

    Article  Google Scholar 

  18. Papazoglou MP (2003) Service-oriented computing: Concepts, characteristics and directions. In: Web Information Systems Engineering, 2003. WISE 2003. Proceedings of the Fourth International Conference on, 2003. IEEE:3–12.

  19. Papazoglou MP, Traverso P, Dustdar S, Leymann F (2008) Service-oriented computing: a research roadmap. Int J Cooperative Information Systems 17(2):223–255

    Article  Google Scholar 

  20. Park Y, Chen JV (2007) Acceptance and adoption of the innovative use of smartphone. Industrial Management & Data Systems 107(9):1349–1365

    Article  Google Scholar 

  21. Park J-H, Park W-I, Kim Y-K, Kang J-H (2009) A personalized device recommender system in Ubiquitous environments. In: Intelligent Networking and Collaborative Systems, 2009. INCOS'09. International Conference on, 2009. IEEE:175–179.

  22. Rowley J (2006) An analysis of the e-service literature: towards a research agenda. Internet Res 16(3):339–359

    Article  Google Scholar 

  23. Sohrabi S, Prokoshyna N, McIlraith SA (2006) Web service composition via generic procedures and customizing user preferences. In: The Semantic Web-ISWC 2006. Springer:597–611.

  24. Svensson D, Hedin G, Magnusson B (2007) Pervasive applications through scripted assemblies of services. IEEE International Conference on Pervasive Services 2007:301–307

    Article  Google Scholar 

  25. ter Beek M, Bucchiarone A, Gnesi S (2006) A survey on service composition approaches: From industrial standards to formal methods. Technical Report 2006-TR-15.

  26. Venkatasubramanian N, Nahrstedt K (1997) An integrated metric for video QoS. In: Proceedings of the fifth ACM international conference on Multimedia, 1997. ACM:371–380

  27. Wang X, Vitvar T, Kerrigan M, Toma I (2006) A qos-aware selection model for semantic web services. In: Service-Oriented Computing–ICSOC 2006. Springer:90–401.

  28. Yu T, Lin K-J (2005) Service selection algorithms for Web services with end-to-end QoS constraints. Information Systems and E-Business Manag 3(2):103–126

    Article  MathSciNet  Google Scholar 

  29. Zeng L, Benatallah B, Ngu AH, Dumas M, Kalagnanam J, Chang H (2004) QoS-aware middleware for web services composition. Software Engineering, IEEE Transactions 30(5):311–327

    Article  Google Scholar 

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Acknowledgements

This research was supported by the Next-Generation Information Computing Development Program through the National Research Foundation of Korea (NRF), funded by the Ministry of Science, ICT & Future Planning (No. 2012M3C4A7032185).

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Correspondence to Jiamei Tang.

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Tang, J., Kim, S. A Service-oriented device selection solution based on user satisfaction and device performance in a ubiquitous environment. Multimed Tools Appl 74, 10761–10783 (2015). https://doi.org/10.1007/s11042-014-2205-x

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