A Taxonomy of Issues, Challenges and Applications in Internet of Multimedia Things (IoMMT)

G. Rama Subba Reddy*, M. Ajay kumar**, N. V. Kishore kumar***
* Department of Computer Science & Engineering, Mother Theresa Institute of Engineering & Technology, Palamaner, Andhra Pradesh, India.
** Department of Electronics and Communication Engineering, Chaitanya Bharathi Institute of Technology, Proddatur, Andhra Pradesh, India.
*** Department of Electrical and Electronics Engineering, Mother Theresa Institute of Engineering & Technology, Palamaner, Andhra Pradesh, India.
Periodicity:January - June'2019
DOI : https://doi.org/10.26634/jcc.6.1.16178


In IoT technology, Multimedia big data which is said to be the large amount of data from multimedia devices will be generated with the fast growth of the multimedia gadgets. The IoT systems are failed in realizing the multimedia devices connectivity unless they are able in processing multimedia gadgets at a time. In contrast, earlier activities concerning research and development concentrate on the scaling strategies to sensor information gathered from many IoT gadgets. Nonetheless the present activities of development and the research do not made mandatory about the features of connectivity between the objects of multimedia. In this paper, we mainly concentrated on the above issue by considering the IoT concept and the advantages are taken to sight towards the IoMMT’s (Internet of Multimedia Things) vision. This paper describes the classification of computing the multimedia big data and also the challenges in models of multimedia computing along with the applications of IoT are discussed. . In addition to this we presented the taxonomy of Multimedia Things (MMT) along with the current research challenges like heterogeneity, reliability, scalability, and accessibility and Quality of Service requirements.


IoT, Multimedia Computing, MMT, IoMMT, issue and challenges

How to Cite this Article?

Reddy, G. R. S., Kumar, M. A., Kumar, N. V. K.(2019).A Taxonomy of Issues, Challenges and Applications in Internet of Multimedia Things (IoMMT), i-manager's Journal on Cloud Computing, 6(1), 1-8. https://doi.org/10.26634/jcc.6.1.16178


[1]. Aazam, M., & Huh, E. N. (2016). Fog computing: The cloud-iot\/ioe middleware paradigm. IEEE Potentials, 35(3), 40-44.
[2]. Alvi, S. A., Afzal, B., Shah, G. A., Atzori, L., & Mahmood, W. (2015). Internet of multimedia things: Vision and challenges. Ad Hoc Networks, 33, 87-111.
[3]. Aslanpour, M. S., Ghobaei-Arani, M., & Toosi, A. N. (2017). Auto-scaling web applications in clouds: A costaware approach. Journal of Network and Computer Applications, 95, 26-41.
[4]. Bui, D. M., Yoon, Y., Huh, E. N., Jun, S., & Lee, S. (2017). Energy efficiency for cloud computing system based on predictive optimization. Journal of Parallel and Distributed Computing, 102, 103-114.
[5]. Caron, E., Desprez, F., & Muresan, A. (2010, November). Forecasting for grid and cloud computing on-demand resources based on pattern matching. In 2010 IEEE Second International Conference on Cloud Computing Technology and Science (pp. 456-463). IEEE.
[6]. Ghomi, E. J., Rahmani, A. M., & Qader, N. N. (2017). Load-balancing algorithms in cloud computing: A survey. Journal of Network and Computer Applications, 88, 50- 71.
[7]. Hameed, A., Khoshkbarforoushha, A., Ranjan, R., Jayaraman, P. P., Kolodziej, J., Balaji, P., ... & Khan, S. U. (2016). A survey and taxonomy on energy efficient resource allocation techniques for cloud computing systems. Computing, 98(7), 751-774.
[8]. Hourdakis, J., Morris, T., Michalopoulos, P., & Wood, K. (2005). Advanced portable wireless measurement and observation station. Final Report, University of Minneseta.
[9]. Kawamura, A., Yoshimitsu, Y., Kajitani, K., Naito, T., Fujimura, K., & Kamijo, S. (2011, October). Smart camera network system for use in railway stations. In 2011 IEEE International Conference on Systems, Man, and Cybernetics (pp. 85-90). IEEE.
[10]. Kumari, A., Tanwar, S., Tyagi, S., Kumar, N., Maasberg, M., & Choo, K. K. R. (2018). Multimedia big data computing and Internet of Things applications: A taxonomy and process model. Journal of Network and Computer Applications, 124, 169-195.
[11]. Leader, S. (2004). Telecommunications handbook for transportation professionals: The basics of telecommunications (No. FHWA-HOP-04-034). United States. Federal Highway Administration.
[12]. Li, N., Yan, B., Chen, G., Govindaswamy, P., & Wang, J. (2010). Design and implementation of a sensor-based wireless camera system for continuous monitoring in assistive environments. Personal and Ubiquitous Computing, 14(6), 499-510.
[13]. Luo, N. (2011). A wireless traffic surveillance system using video analytics (Doctoral dissertation, University of North Texas).
[14]. Manvi, S. S., & Shyam, G. K. (2014). Resource management for Infrastructure as a Service (IaaS) in cloud computing: A survey. Journal of Network and Computer Applications, 41, 424-440.
[15]. Sahni, Y., Cao, J., Zhang, S., & Yang, L. (2017). Edge Mesh: A new paradigm to enable distributed intelligence in Internet of Things. IEEE Access, 5, 16441-16458.
[16]. Sharkh, M. A., & Shami, A. (2017). An evergreen cloud: Optimizing energy efficiency in heterogeneous cloud computing architectures. Vehicular Communications, 9, 199-210.
[17]. Sun, L. N. (2014). Building intelligent parking lot based on RFID and cloud computing technology. In Advanced Materials Research (Vol. 846, pp. 1550-1553). Trans Tech Publications.
[18]. Vázquez-Poletti, J. L., Moreno-Vozmediano, R., Han, R., Wang, W., & Llorente, I. M. (2017). SaaS enabled admission control for MCMC simulation in cloud computing infrastructures. Computer Physics Communications, 211, 88-97.
[19]. Wang, W., De, S., Toenjes, R., Reetz, E., & Moessner, K. (2012, June). A comprehensive ontology for knowledge representation in the internet of things. In 2012 IEEE 11th International Conference on Trust, Security and Privacy in Computing and Communications (pp. 1793- 1798). IEEE.
[20]. Zhu, W., Zhuang, Y., & Zhang, L. (2017). A three-dimensional virtual resource scheduling method for energy saving in cloud computing. Future Generation Computer Systems, 69, 66-74.

Purchase Instant Access

Single Article

North Americas,UK,
Middle East,Europe
India Rest of world
Pdf 35 35 200 20
Online 35 35 200 15
Pdf & Online 35 35 400 25

If you have access to this article please login to view the article or kindly login to purchase the article
Options for accessing this content:
  • If you would like institutional access to this content, please recommend the title to your librarian.
    Library Recommendation Form
  • If you already have i-manager's user account: Login above and proceed to purchase the article.
  • New Users: Please register, then proceed to purchase the article.