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QoS-Aware Selection of IoT-Based Service

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Abstract

With the proliferation of a number of IoT-based service providers in the market, it would be difficult to select a suitable IoT service as per the requirement among the vast pool of available services showing similar capabilities. Quality-of-service (QoS) parameters that define a service may be used for doing an appropriate selection. Here we consider IoT as the composition of its three possible components: Things, communication entity and computing entity, and description of an IoT may include QoS parameters for each of these components. We propose a framework that makes use of a multi-criteria decision making (MCDM) as a combination of known approaches under the names Analytic Hierarchy Process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) for conducting the selection process where QoS parameters of various component of IoT act as criteria. We demonstrate the effectiveness of the proposed approach along with the sensitivity analysis for showing the robustness of the proposed framework.

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References

  1. Townsend, J.: The Function of Quality Assurance (QA) with the Internet of Things, https://www.ctl.io/blog/post/qa-with-the-iot/. Accessed 30 June 2018

  2. Morgan, J.: A Simple Explanation Of “The Internet Of Things,” https://www.forbes.com/sites/jacobmorgan/2014/05/13/simple-explanation-internet-things-that-anyone-can-understand/#679a507e1d09. Accessed 29 May 2019

  3. Guinard, D.T.; Vlad, K.; Stamatis, S.; Patrik, S.D.: Interacting with the SOA-based internet of things: discovery, query, selection, and on-demand provisioning of web services. IEEE Trans. Serv. Comput. 3, 223–235 (2010). https://doi.org/10.1109/tsc.2010.3

    Article  Google Scholar 

  4. Da Xu, L.; He, W.; Li, S.: Internet of things in industries : a survey. IEEE Trans. Ind. Inf. 10, 2233–2243 (2014). https://doi.org/10.1109/tii.2014.2300753

    Article  Google Scholar 

  5. Ray, P.P.: A survey on Internet of Things architectures. J. King Saud Univ. Comput. Inf. Sci. 30, 291–319 (2018). https://doi.org/10.1016/j.jksuci.2016.10.003

    Article  Google Scholar 

  6. Kanagaraju, P.; Nallusamy, R.: Registry service selection based secured Internet of Things with imperative control for industrial applications. Clust. Comput. 22, 12507–12519 (2019). https://doi.org/10.1007/s10586-017-1678-6

    Article  Google Scholar 

  7. Kumar, A.D.V.; Arockiam, L.: TOPQoS: TENSOR based optimum path selection in Internet of Things to enhance quality of service. Int. J. Sci. Res. Comput. Sci. Eng. Inf. Technol. 2, 852–859 (2017)

    Google Scholar 

  8. Naseri, A.; Jafari Navimipour, N.: A new agent-based method for QoS-aware cloud service composition using particle swarm optimization algorithm. J. Ambient Intell. Humaniz. Comput. 10, 1851–1864 (2019). https://doi.org/10.1007/s12652-018-0773-8

    Article  Google Scholar 

  9. Ghosh, A.; Sarkar, S.: Pricing for profit in Internet of Things. IEEE Trans. Netw. Sci. Eng. (2018). https://doi.org/10.1109/TNSE.2018.2796592

    Article  Google Scholar 

  10. Singh, M.; Baranwal, G.: Quality of Service (QoS) in Internet of Things. In: 2018 3rd International Conference On Internet of Things: Smart Innovation and Usages (IoT-SIU). pp. 1–6. IEEE (2018)

  11. Ebrahimi, M.; Shafiei, B.E.; Wong, R.K.; Fong, S.; Fiaidhi, J.: An adaptive meta-heuristic search for the internet of things. Future Gener. Comput. Syst. 76, 486–494 (2017)

    Article  Google Scholar 

  12. Nithya, K.K.; Prathap M.V.; Babu K.R.: Cluster oriented sensor selection for context-aware Internet of Things applications. In: International Conference on Intelligent Data Communication Technologies and Internet of Things. pp. 981–988. Springer (2018)

  13. Perera, C.; Zaslavsky, A.; Christen, P.; Compton, M.; Georgakopoulos, D.: Context-aware sensor search, selection and ranking model for internet of things middleware. In: 2013 IEEE 14th international conference on mobile data management. pp. 314–322. IEEE (2013)

  14. Mekala, M.S.; Viswanathan, P.: Energy-efficient virtual machine selection based on resource ranking and utilization factor approach in cloud computing for IoT. Comput. Electr. Eng. 73, 227–244 (2019). https://doi.org/10.1016/j.compeleceng.2018.11.021

    Article  Google Scholar 

  15. Emami, M.; Saeed, K.; Motamedi, S.A.: Virtual sensor as a service: a new multicriteria QoS-aware cloud service composition for IoT applications. J. Supercomput. 74, 5485–5512 (2018). https://doi.org/10.1007/s11227-018-2454-y

    Article  Google Scholar 

  16. Nef, M.-A.; Perlepes, L.; Karagiorgou, S.; Stamoulis, G.I.; Kikiras, P.K.: Enabling QoS in the Internet of Things. In: Proceedings of the 5th Int. Conference on Communication, Theory, Reliability, and Quality of Service (CTRQ 2012). pp. 33–38 (2012)

  17. Tanganelli, G.; Vallati, C.; Mingozzi, E.: Ensuring quality of service in the Internet of Things. In: New Advances in the Internet of Things. pp. 139–163 (2018)

  18. Duan, R.; Chen, X.; Xing, T.: A QoS architecture for IOT. In: 2011 International Conference on Internet of Things and 4th International Conference on Cyber, Physical and Social Computing. pp. 717–720. IEEE (2011)

  19. Li, L.; Li, S.; Zhao, S.: QoS-Aware scheduling of services-oriented internet of things. IEEE Trans. Ind. Inf. 10, 1497–1507 (2014). https://doi.org/10.1109/TII.2014.2306782

    Article  Google Scholar 

  20. Buyya, R.; Dastjerdi, A.V.: Internet of Things: Principles and Paradigms. Elsevier, London (2016)

    Google Scholar 

  21. Jin, X.; Chun, S.; Jung, J.; Lee, K.-H.: A fast and scalable approach for IoT service selection based on a physical service model. Inf. Syst. Front. 19, 1357–1372 (2017). https://doi.org/10.1007/s10796-016-9650-1

    Article  Google Scholar 

  22. Alsaryrah, O.; Mashal, I.; Chung, T.-Y.: Energy-aware services composition for Internet of Things. In: 2018 IEEE 4th World Forum on Internet of Things (WF-IoT). pp. 604–608. IEEE (2018)

  23. Xiang, C.; Yang, P.; Wu, X.; He, H.; Xiao, S.: QoS-based service selection with lightweight description for large-scale service-oriented Internet of Things. Tsinghua Sci. Technol. 20, 336–347 (2015)

    Article  Google Scholar 

  24. Khanouche, M.E.; Amirat, Y.; Chibani, A.; Kerkar, M.; Yachir, A.: Energy-centered and QoS-aware services selection for Internet of Things. IEEE Trans. Autom. Sci. Eng. 13, 1256–1269 (2016). https://doi.org/10.1109/tase.2016.2539240

    Article  Google Scholar 

  25. Ashraf, Q.M.; Habaebi, M.H.; Islam, M.R.: TOPSIS-based service arbitration for autonomic Internet of Things. IEEE Access. 4, 1313–1320 (2016). https://doi.org/10.1109/ACCESS.2016.2545741

    Article  Google Scholar 

  26. Hsu, Y.-C.; Lin, C.-H.; Chen, W.-T.: Design of a sensing service architecture for Internet of Things with semantic sensor selection. In: 2014 IEEE 11th International Conference on Ubiquitous Intelligence and Computing and 2014 IEEE 11th International Conference on Autonomic and Trusted Computing and 2014 IEEE 14th International Conference on Scalable Computing and Communications and its Associated Workshops. pp. 290–298. IEEE (2014)

  27. Giacobbe, M.; Pietro, R.D.; Zaia, A.; Puliafito, A.: The internet of things in oil and gas industry: a multi criteria decision making brokerage strategy. In: Special Issue, 4th International Conference on Automation, Control Engineering and Computer Science (ACECS 2017), Proceedings of Engineering and Technology-PET. pp. 47–52 (2017)

  28. Qi, L.; Dai, P.; Yu, J.; Zhou, Z.; Xu, Y.: “Time–Location–Frequency”–aware Internet of things service selection based on historical records. Int. J. Distrib. Sens. Netw. 13, 1550 (2017). https://doi.org/10.1177/1550147716688696

    Article  Google Scholar 

  29. Singla, C.; Mahajan, N.; Kaushal, S.; Verma, A.; Sangaiah, A.K.: Modelling and Analysis of Multi-objective Service Selection Scheme in IoT-Cloud Environment. In: Cognitive Computing for Big Data Systems Over IoT. pp. 63–77. Springer (2018)

  30. Kim, S.: R-learning-based team game model for Internet of things quality-of-service control scheme. Int. J. Distrib. Sens. Netw. 13, 1550147716687558 (2017). https://doi.org/10.1177/1550147716687558

    Article  Google Scholar 

  31. Al-Fuqaha, A.; Guizani, M.; Mohammadi, M.; Aledhari, M.; Ayyash, M.: Internet of Things: a survey on enabling technologies, protocols, and applications. IEEE Commun. Surv. Tutor. 17, 2347–2376 (2015). https://doi.org/10.1109/COMST.2015.2444095

    Article  Google Scholar 

  32. Khan, R.; Khan, S.U.; Zaheer, R.; Khan, S.: Future internet: the internet of things architecture, possible applications and key challenges. In: 2012 10th international conference on frontiers of information technology. pp. 257–260. IEEE (2012)

  33. Gluhak, A.; Krco, S.; Nati, M.; Pfisterer, D.; Mitton, N.; Razafindralambo, T.: A survey on facilities for experimental Internet of Things research. IEEE Commun. Mag. 49, 58–67 (2011). https://doi.org/10.1227/01.neu.0000297013.35469.37

    Article  Google Scholar 

  34. Gridelli, B.S.: How to calculate network availability?, https://netbeez.net/blog/how-to-calculate-network-availability/. Accessed 29 May 2019

  35. Weber, R.H.: Internet of Things—new security and privacy challenges. Comput. Law Secur. Rev. 26, 23–30 (2010). https://doi.org/10.1016/j.clsr.2009.11.008

    Article  Google Scholar 

  36. Chalmers, D.; Sloman, M.: A survey of quality of service in mobile computing environments. IEEE Commun. Surv. Tutor. 2, 2–10 (1999). https://doi.org/10.1109/comst.1999.5340514

    Article  Google Scholar 

  37. Salih, Y.K.; See, O.H.; Ibrahim, R.W.; Yussof, S.; Iqbal, A.: A network selection indicator based on golden relation between monetary cost and bandwidth in heterogeneous wireless networks. Res. J. Appl. Sci. Eng. Technol. 7, 478–483 (2014). https://doi.org/10.19026/rjaset.7.279

    Article  Google Scholar 

  38. Fang, J.; Hu, S.; Han, Y.: A service interoperability assessment model for service composition. In: 2004 IEEE International Conference on Services Computing. pp. 153–158. IEEE (2004)

  39. ETSI, http://www.etsi.org/about/how-we-work/testing-and-interoperability

  40. Karakus, M.; Durresi, A.: Quality of Service (QoS) in software defined networking (SDN): a survey. J. Netw. Comput. Appl. 80, 200–218 (2017). https://doi.org/10.1016/j.jnca.2016.12.019

    Article  Google Scholar 

  41. Chalmers, D.; Sloman, M.: Survey of Quality of Service in mobile computing environments. IEEE Commun. Surv. 2, 2–10 (1999). https://doi.org/10.1109/comst.1999.5340514

    Article  Google Scholar 

  42. Ducq, Y.; Chen, D.: How to measure interoperability: concept and approach. 2008 IEEE International Technology Management Conference (ICE). pp. 1–8 (2008)

  43. Kaczmarek, P.L.: Interoperability constraints in service selection algorithms. In: ENASE 2012—Proceedings of the 7th International Conference on Evaluation of Novel Approaches to Software Engineering. pp. 23–32 (2012). https://doi.org/10.5220/0003980500230032

  44. Kalantar-zadeh, K.: Sensors: An Introductory Course. Springer (2013)

  45. CLOUD IOT CORE, https://cloud.google.com/iot-core/

  46. LION PRECISION: Understanding Sensor Resolution Specifications and Performance. pp. 1–6 (2014)

  47. Garg, S.K.; Versteeg, S.; Buyya, R.: A framework for ranking of cloud computing services. Future Gener. Comput. Syst. 29, 1012–1023 (2013). https://doi.org/10.1016/j.future.2012.06.006

    Article  Google Scholar 

  48. Habib, S.M.; Ries, S.; Muhlhauser, M.: Cloud computing landscape and research challenges regarding trust and reputation. In: 2010 7th International Conference on Ubiquitous Intelligence and Computing and 7th International Conference on Autonomic and Trusted Computing. pp. 410–415. IEEE (2010)

  49. Martin, P.; Xu, Z.; Martin, P.; Powley, W.; Zulkernine, F.: Reputation-enhanced QoS-based web services discovery reputatio. In: IEEE International Conference on Web Services (ICWS 2007). pp. 249–256 (2007)

  50. Alunkal, B.; Veljkovic, I.; Von Laszewski, G.; Amin, K.: Reputation-based grid resource selection. In: Proceedings of AGridM. pp. 432–438 (2003)

  51. Satty, T.: The Analytic Hierarchy Process. McGrawHill, New York (1980)

    Google Scholar 

  52. Whaiduzzaman, M.D.; Gani, A.; Anuar, Nor B.; Shiraz, M.; Haque, M.N.; Haque, I.T.: Cloud service selection using multicriteria decision analysis. Sci. World J. (2014). https://doi.org/10.1155/2014/459375

  53. Deng, H.; Yeh, C.-H.; Willis, R.J.: Inter-company comparison using modified TOPSIS with objective weights. Comput. Oper. Res. 27, 963–973 (2000). https://doi.org/10.1016/S0305-0548(99)00069-6

    Article  MATH  Google Scholar 

  54. Zaeri, M.S.; Sadeghi, A.; Naderi, A.; Kalanaki, A.: Application of multi-criteria decision making technique to evaluation suppliers in supply chain management. Afr. J. Math. Comput. Sci. Res. 4, 100–106 (2011)

    Google Scholar 

  55. Ranjan, R.; Siba, K.; Chiranjeev, M.: A novel framework for cloud service evaluation and selection using hybrid MCDM methods. Arab. J. Sci. Eng. 43, 7015–7030 (2018). https://doi.org/10.1007/s13369-017-2975-3

    Article  Google Scholar 

  56. Hossain, M.S.; Muhammad, G.: Cloud-assisted Industrial Internet of Things (IIoT)—enabled framework for health monitoring. Comput. Netw. 101, 192–202 (2016). https://doi.org/10.1016/j.comnet.2016.01.009

    Article  Google Scholar 

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Correspondence to Gaurav Baranwal.

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Singh, M., Baranwal, G. & Tripathi, A.K. QoS-Aware Selection of IoT-Based Service. Arab J Sci Eng 45, 10033–10050 (2020). https://doi.org/10.1007/s13369-020-04601-8

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