Mobile Networks and Applications

, Volume 24, Issue 2, pp 365–374 | Cite as

A Novel Research on the Influence of Enterprise Culture on Internal Control in big Data and Internet of Things

  • Haijun LiuEmail author
  • Xiaobing Liu


The effective management of enterprise resources in internet of things is a growing research trend in modern era. The big data concept influences more opportunities to the researchers to exhibit their innovations in various application oriented fields. The academic and organizational researches suggested that big data provides more benefits on sustained basis for the committed resource management environment. The study shows positive and active enterprise culture is positively correlated to effective internal control. In the enhancement of these resource management initiatives, the dynamic capability of the data and its assumptions are considered. In the case of enterprise culture the implication of practical and business limitations and advantages are discussed in this article. The intellectual contributions and the poles of excellence on the field of big data is a common platform upon which several communication components in practice on every day use which are interfaced and interconnected. In general IoT reduces the distance between the real world and internet by incorporating and integrating different perspectives of technology such as pervasive computing, data communication, networking, sensor node communication etc.,


Internet of things (IoT) Big data Internal control 



This paper is supported by the National Science and Technology Support Program: "R & D and application of key technology for high-end equipment manufacturing". (2012BAF12B08)


  1. 1.
    Batalla JM, Krawiec P (2014) Conception of ID layer performance at the network level for internet of things. Springer Pers Ubiquit Comput 18:465–480Google Scholar
  2. 2.
    Wang H, Wang J (2014) November. An effective image represen- tation method using kernel classification. In: tools with artificial intelligence (ICTAI), 2014 I.E. 26th international conference on. IEEE, pp 853–858Google Scholar
  3. 3.
    Khan Z, Anjum A, Kiani SL (2013) Cloud based big data analytics for future cities. In: Proc Conference on utility and cloud computing IEEE Computer Society, pp 381–386Google Scholar
  4. 4.
    Guerrero-ibanez JA, Zeadally S, Castillo JC (2015) Integration challenges of intelligent transportation systems with connected vehicle, cloud computing, and internet of things technologies. IEEE Wirel Commun 22(6):122–128Google Scholar
  5. 5.
    Mohamed N, Al-Jaroodi J, Real-time big data analytics: applications and challenges. High Performance Computing & Simulation (HPCS), 2014 International Conference on, 2: 305–310, 2014Google Scholar
  6. 6.
    Gendreau AA, Moorman M (2016) Survey of intrusion detection systems towards an end to end secure internet of things. Proceedings of international conference on future internet of things and cloudGoogle Scholar
  7. 7.
    Aloi G et al (2014) STEM-net: an evolutionary network architecture for smart and sustainable cities. Trans on Emerging Telecommunications Technologies 25(1):21–40Google Scholar
  8. 8.
    Marie P, Lim L, Manzoor A, Chabridon S, Conan D, Desprats T (2014) QoC-aware context data distribution in the internet of things. In: Proceedings of the 1st ACM workshop on middleware for context-aware applications in the IoT, Bordeaux, France 2, pp 13–18Google Scholar
  9. 9.
    Cárdenas AA, Manadhata PK, Rajan SP (2013) Big data analytics for security. IEEE Secur Priv 11(6):74–76Google Scholar
  10. 10.
    Giannikos M, Kokoli K, Fotiou N, Marias GF, Polyzos GC (2013) Towards secure and context-aware information lookup for the internet of things. In: Proceedings of the 2013 international conference on computing, networking and communications (ICNC). San Diego, CA, USA, pp 28–31Google Scholar
  11. 11.
    Mohamed N, Al-Jaroodi J, Real-time big data analytics: applications and challenges. High Performance Computing & Simulation (HPCS), 2014 International Conference on, 2: 305–310, 2014Google Scholar
  12. 12.
    Bruno R, Nurchis M (2013) Robust and efficient data collection schemes for vehicularmultimedia sensor networks. In: Proceedings of the IEEE 14th international symposium and workshops on world of wireless, mobile and multimedia networks (WoWMoM). Spain, Madrid, pp 1–10Google Scholar
  13. 13.
    Aazam M, Khan I, Alsaffar AA, Huh E-N (2014) Cloud of things: integrating internet of things and cloud computing and the issues involved. In: Proc. 11th Int. Bhurban Conf. Appl. Sci. Technol. (IBCAST), Islamabad, Pakistan, pp 414–419Google Scholar

Copyright information

© Springer Science+Business Media, LLC 2017

Authors and Affiliations

  1. 1.Faculty of Management &EconomicsDalian University of TechnologyDalianChina

Personalised recommendations