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Challenges and research directions for Internet of Things

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Abstract

The emergence of Internet of Things (IoT) is empowered by the availability of the high volume of smart sensors, Radio Frequency Identification, a suitable communication technologies and protocols. In the near future, the Internet will be full of heterogeneous connected devices. In recent years, the IoT has drawn significant attention as it can solve difficult problems. However, the heterogeneity of devices and the large scale networks expose the IoT to many challenges that must be addressed; otherwise, the systems performance will deteriorate. As an attempt to identify these challenges, this paper comprehensibly cites the main IoT concepts, the serious IoT challenges and the quality of services presented in the recent literature. It also investigates the corresponding main research directions and the proposed solutions. This paper can increase the knowledge of the reader since it is the first IoT survey that presents load balancing algorithms utilized in solving the extreme data storage challenge.

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References

  1. Micrium, Part 1: IoT devices and local networks | Micrium, https://www.micrium.com/iot/devices/. Accessed 14 May 2016.

  2. Silva, I., Leandro, R., Macedo, D., & Guedes, L. (2013). A dependability evaluation tool for the Internet of Things. Computers & Electrical Engineering, 39(7), 2005–2018.

    Article  Google Scholar 

  3. Li, S., Xu, L., & Zhao, S. (2014). The internet of things: A survey. Information Systems Frontiers, 17(2), 243–259.

    Article  Google Scholar 

  4. Lee, I., & Lee, K. (2015). The Internet of Things (IoT): Applications, investments, and challenges for enterprises. Business Horizons, 58(4), 431–440.

    Article  Google Scholar 

  5. Internet of Things and future internet enterprise systems, http://cordis.europa.eu/fp7/ict/enet/rfid-iot_en.html. Accessed 5 March 2016.

  6. Philip, J., & Koopman, Jr. (1996). Embedded system design issues (The rest of the story). In Proceedings of the International Conference on Computer Design (ICCD 96) in Computers and Processors, October 7–9 1996, (p. 310).

  7. INFSO D.4NETWORKED ENTERPRISE & RFID INFSO G.2 Micro & Nanosystems. In Co-operation with the RFID Working Group of the ETP EPOSS, Internet of Things in 2020, Roadmap for the Future, Version 1.1, May 27. (2008). Resource document. http://www.smart-systems Things_in_2020_EC-EPoSS_Workshop_Report_2008_v3.pdf . Accessed 17 April 2016.

  8. ITU: Committed to connecting the world, http://www.itu.int/en/ITUT/gsi/iot/Pages/default.aspx. Accessed 18 May 2016.

  9. Gubbi, J., Buyya, R., Marusic, S., & Palaniswami, M. (2013). Internet of Things (IoT): A vision, architectural elements, and future directions. Future Generation Computer Systems, 29(7), 1645–1660.

    Article  Google Scholar 

  10. Al-Fuqaha, A., Guizani, M., Mohammadi, M., Aledhari, M., & Ayyash, M. (2015). Internet of Things: A survey on enabling technologies, protocols, and applications. IEEE Communications Surveys & Tutorials, 17(4), 2347–2376.

    Article  Google Scholar 

  11. Evans, D. (2011). The Internet of Things how the next evolution of the internet is changing everything , White paper 2011, Cisco Internet Business Solutions Group (IBSG), US, pp. 1-11. Resource document. https://www.cisco.com/c/dam/en_us/about/ac79/docs/innov/IoT_IB-SG_0411FINAL.pdf. Accessed 7 March 2016.

  12. Khan, R., Khan, S. U., Zaheer, R., & Khan, S. (2012). Future internet: The internet of things architecture, possible applications and key challenges. In 10th International Conference on Frontiers of Information Technology (FIT): Proceedings (pp. 257–260).

  13. Herrera-Quintero, F., Macià-Pérez, F., Marcos-Jorquera, D., & Gilart-Iglesias, V. (2012). Wireless sensor networks and service-oriented architecture, as suitable approaches to be applied into ITS. In Proceedings of Telematics and Information Systems (EATIS), 2012 6th Euro American Conference (pp. 301–308).

  14. Minerva, R., Biru, A., & Rotondi, D. (2015). Towards a definition of the Internet of Things (IoT). Italia:IEEE 2015, pp. 1-86. Resource document. http://iot.ieee.org/images/files/pdf/IEEE_IoT_Towards_Definition_Internet_of_Things_Revision1_27MAY15.pdf. Accessed 5 January 2016

  15. Aberer, K., Hauswirth, M., & Salehi, A. (2006). The Global Sensor Networks middleware for effcient an fexible deployment and interconnection of sensor networks. Switzerland: School of Computer and Communication Sciences Ecole Polytechnique Fdrale de Lausanne (EPFL) CH-1015 Lausanne 2006:1-21. Resource document. http://lsirpeople.epfl.ch/hauswirth/papers/LSIR-REPORT-2006-006.pdf. Accessed 2 May 2016.

  16. datatracker, Constrained RESTful Environments (core), https://datatracker.ietf.org/wg/core/charter/. Accessed 08 Nov 2016.

  17. Micrium, IoT standards and protocols, http://www.postscapes.com/internet-of-things-protocols/ accessed 20 Aug 2016.

  18. Colitti, W., Steenhaut, K., De Caro, N., Buta, B., & Dobrota, V. (2011). Evaluation of constrained application protocol for wireless sensor networks. In Proc. 18th IEEE Workshop LANMAN 2011 (pp 1–6).

  19. Hui, J., & Culler, D. (2008). Extending IP to low-power, wireless personal area networks. IEEE Internet Computing, 12(4), 37–45.

    Article  Google Scholar 

  20. IEEE standard for low-rate wireless networks, IEEE Std 802.15.4 TM-2015.

  21. Le, H., Guyennet, H., & Felea, V. (2007). OBMAC: an Overhearing Based MAC Protocol for Wireless Sensor Networks. In SENSORCOMM 07 Proceedings of the 2007 International Conference on Sensor Technologies and Applications (pp. 547–553).

  22. Guglielmo, D., Brienza, S., & Anastasi, G. (2016). IEEE 802.15.4e: A survey. Computer Communications, 88, 1–24.

    Article  Google Scholar 

  23. Hammoudi, S., Benaouda, A., Harous, S., & Aliouat, Z. (2016). Load balancing in the cloud using specialization. In Proceedings of Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON), (pp. 1–7).

  24. Timothy, R. P., Nawajish, N., Deng, D., & John, B. G. (2016). Flood forecasting GIS water-flow visualization enhancement (WaVE): A case study. Journal of Geographic Information System, 8, 692–728.

    Article  Google Scholar 

  25. pubnub, https://www.pubnub.com/. Accessed 16 March 2017.

  26. adafruit, https://www.adafruit.com/product/2718. Accessed 16 March 2017.

  27. Sensor Web Enablement (SWE), http://www.opengeospatial.org/ogc/markets-technologies/swe. Accessed 16 March 2017.

  28. Botta, A., Donato, W., Persico, V., & Pescapé, A. (2016). Integration of cloud computing and Internet of Things: A survey. Future Generation Computer Systems, 56, 684–700.

    Article  Google Scholar 

  29. Barnatt C, Cloud Computing, http://explainingcomputers.com/cloud.html. Accessed 14 May 2016.

  30. Amin, Z., Singh, H., & Sethi, N. (2015). Review on fault tolerance techniques in cloud computing. International Journal of Computer Applications, 116(18), 11–17.

    Article  Google Scholar 

  31. Zhang, Q., Cheng, L., & Boutaba, R. (2016). Cloud computing: state-of-the-art and research challenges. Journal of internet services and applications, 1(4), 7–18.

    Google Scholar 

  32. Stankovic, J. (2014). Research directions for the internet of things. IEEE Internet of Things Journal, 1(1), 3–9.

    Article  Google Scholar 

  33. Kanuparthi, A., Karri, R., & Addepalli, S. (2013). Hardware and embedded security in the context of Internet of Things. In CyCAR ’13 Proceedings of the 2013 ACM workshop on Security, privacy & dependability for cyber vehicles, Berlin, Germany, ACM 2013, (pp. 61–64).

  34. Sun, Y., Song, H. J., JARA, A., & BIE, R. (2016). Internet of things and big data analytics for smart and connected communities. IEEE Access, 4, 766–773.

    Article  Google Scholar 

  35. Chen, H., Gulati, H., Kung, H., & Teerapittayanon S. (2015). Compressive wireless pulse sensing. In Proceedings of Collaboration Technologies and Systems (CTS), 2015 International Conference on 1–5 June 2015, IEEE, Atlanta, GA, (pp. 5–11).

  36. Barnatt, C. Big Data, http://www.explainingcomputers.com/big_d-ata.html. Accessed 7 May 2016.

  37. Baccarelli, E., Cordeschi, N., Mei, A., Panella, M., Shojafar, M., & Stefa, J. (2016). Energy-efficient dynamic traffic offloading and reconfiguration of networked data centers for big data stream mobile computing: Review, challenges, and a case study. IEEE Network, 30(2), 54–61.

    Article  Google Scholar 

  38. Kaur, R., & Luthra, P. (2014) Load balancing in cloud computing. In Proceedings of International Conference on Recent Trends. Information, Telecommunication and Computing, ITC , Association of Computer Electronics and Electrical Engineers (ACEEE) (pp. 1–8).

  39. Vakkalanka, S. (2012). A classification of job scheduling algorithms for balancing load on web servers. International Journal of Modern Engineering Research (IJMER), 2(5), 3679–3683.

    Google Scholar 

  40. Bourke, T. (2001). Server load balancing. Sebastopol, CA: O’Reilly.

    Google Scholar 

  41. Sharma, S., & Godara, J. (2016). Load balancing in cloud computing. International Journal of Computer Systems (ISSN: 2394-1065),03(04), 322–326.

  42. Nema, L., Sharma, A., & Jain, S. (2016). Load balancing algorithms in cloud computing: An extensive survey. International Journal of Engineering Science and Computing, 6(6), 7463–7468.

    Google Scholar 

  43. Patel, I., & Shah, B. (2016). survey on resource allocation technique in cloud. International Journal of Science and Research (IJSR), 5(4), 232–235.

    Article  Google Scholar 

  44. Mishra, S., & Tondon, R. (2016). A shared approach of dynamic load balancing in cloud computing. International Journal of Scientific Research in Science. Engineering and Technology (ijsrset.com), 2(02), 632–638.

    Google Scholar 

  45. Kumar, V., & Kumar, J. (2016). A comparative study of load balancing techniques in cloud computing environment. International Journal of Innovations & Advancement in Computer Science IJIACS, 05(04), 27–32.

    Google Scholar 

  46. Sharma, S., Singh, S., & Sharma, M. (2008). Performance analysis of load balancing algorithms. International Journal of Computer, Electrical, Automation, Control and Information Engineering, 2(2), 367–370.

    Google Scholar 

  47. Kushwaha, M., & Gupta, S. (2015). Various schemes of load balancing in distributed systems—A review. International Journal of Scientific Research Engineering & Technology (IJSRET), 4(7), 741–748.

    Google Scholar 

  48. Ray, S., & Sarkar, A. (2012). Execution analysis of load balancing algorithms in cloud computing environment. International Journal on Cloud Computing: Services and Architecture, 2(5), 1–13.

    Google Scholar 

  49. Mesbahi, M., Hashemi, M., & Rahmani A. (2016). Performance evaluation and analysis of load balancing algorithms in cloud computing environments. In Second International Conference on Web Research (ICWR) (pp. 145–151).

  50. Guyennet, H., Herrmann, B., Philippe, L., & Spies, F. (1994). A performance study of dynamic load balancing algorithms for multicomputers. In Massively Parallel Computing Systems, IEEE, Ischia, (pp. 538–540).

  51. Devi, P. (2013). Implementation of cloud computing by using short job scheduling. International Journal of Advanced Research in Computer Science and Software Engineering, 3(7), 178–183.

    Google Scholar 

  52. Cardellini, V., Colajanni, M., & Yu, P. (1999). Dynamic load balancing on Web-server systems. IEEE Internet Computing, 3(3), 28–39.

    Article  Google Scholar 

  53. Sethi, S., Sahu, A., & Jena, S. (2012). Efficient load Balancing in cloud computing using fuzzy logic. IOSR Journal of Engineering, 02(07), 65–71.

    Article  Google Scholar 

  54. Desai, T., & Prajapati, J. (2013). A survey of various load balancing techniques and challenges in cloud computing. International Journal of Scientific and Technology Research, 2(11), 158–161.

    Google Scholar 

  55. Bhagwan, R., Savage, S., & Voelker, G. (2003). Understanding availability. In F. Kaashoek & I. Stoica (Eds.), Peer-to-peer systems (Vol. II, pp. 256–267). Berlin: Springer.

    Chapter  Google Scholar 

  56. Maalel, N., Natalizio, E., Bouabdallah, A., Roux, P., & Kellil, M. (2013). Reliability for emergency applications in Internet of Things. In Proceedings of the IEEE International Conference on Distributed Computing in Sensor Systems DCOSS May 2013 (pp. 361–366).

  57. Yi, D., & Yang, H. (2016). HEER A delay-aware and energy-efficient routing protocol for wireless sensor Networks. Computer Networks, 104, 155–173.

    Article  Google Scholar 

  58. Shao, X., Wang, C., & Rao, Y. (2015). Network coding aware QoS routing for wireless sensor network. Journal of Communications, 10(01), 24–32.

    Article  Google Scholar 

  59. Li, D., Hao, H., Ji, G., & Zhao, J. (2015). An adaptive clustering algorithm based on improved particle swarm optimisation in wireless sensor networks. International Journal of High Performance Computing and Networking, 8(4), 370–380.

    Article  Google Scholar 

  60. Technical.openmobilealliance.org, http://technical.openmobilealliance.org/Technical/technicalinformation/release-program/current-releases/omalightweightm2mv1-0-2. Accessed 7 March 2016.

  61. Wallin, S., & Wikström, C. (2011). Automating network and service configuration using NETCONF and YANG”. In LISA’11 Proceedings of the 25th International Conference on Large Installation System Administration (p. 22).

  62. Plugtests events, http://www.etsi.org/about/what-we-do/plugtests. Accessed 7 August 2016.

  63. Pursuing ROadmaps and BEnchmarks for the Internet of Things 2013, http://www.probe-it.eu/. Accessed 7 March 2016.

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Correspondence to Sarra Hammoudi.

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Hammoudi, S., Aliouat, Z. & Harous, S. Challenges and research directions for Internet of Things. Telecommun Syst 67, 367–385 (2018). https://doi.org/10.1007/s11235-017-0343-y

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