55
Views
0
CrossRef citations to date
0
Altmetric
Articles

Improving mobile mass monitoring in the IoT environment based on Fog computing using an improved forest optimization algorithm

, &
Pages 36-49 | Received 02 Jan 2022, Accepted 25 Jul 2022, Published online: 04 Aug 2022

References

  • Agarwal, N., Chauhan, S., Kar, A. K., & Goyal, S. (2017). Role of human behaviour attributes in mobile crowd sensing: A systematic literature review. Digital Policy, Regulation and Governance, 19(2), 168–185. https://doi.org/10.1108/DPRG-05-2016-0023
  • Atlam, H., Walters, R., & Wills, G. (2018). Fog computing and the Internet of Things: A review. Big Data and Cognitive Computing, 2(2), 10. https://doi.org/10.3390/bdcc2020010
  • Azmy, S. B., Zorba, N., & Hassanein, H. S. (2018). Quality of coverage: A novel approach to coverage for mobile crowd sensing systems. Global information infrastructure and networking symposium (GIIS), pp. 1-5.
  • Buckley, J. J., & Hayashi, Y. (1994). Fuzzy genetic algorithm and applications. Fuzzy Sets and Systems, 61(2), 129–136. https://doi.org/10.1016/0165-0114(94)90228-3
  • Cai, J., Li, Q., Li, L., Peng, H., & Yang, Y. (2012). A fuzzy adaptive chaotic ant swarm optimization for economic dispatch. International Journal of Electrical Power & Energy Systems, 34(1), 154–160. https://doi.org/10.1016/j.ijepes.2011.09.020
  • Chen, J., & Yang, J. (2019). Maximizing coverage quality with budget constrained in mobile crowdsensing network for environmental monitoring applications. Sensors, 19(10), 2399. https://doi.org/10.3390/s19102399
  • Farahani, H., Ebadi, M., & Jafari, H. (2019). Finding inverse of a fuzzy matrix using eigen value method. International Journal of Innovative Technology and Exploring Engineering, 9(2), 3030–3037. https://doi.org/10.35940/ijitee.B6295.129219
  • Ghaemi, M., & Feizi Derakhshi, M. R. (2014). Forest optimization algorithm. Expert Systems with Applications, 41(15), 6676–6687. https://doi.org/10.1016/j.eswa.2014.05.009
  • Guo, B., Chen, C., Zhang, D., Yu, Z., & Chin, A. (2016). Mobile crowd sensing and computing: When participatory sensing meets participatory social media. IEEE Communications Magazine, 54(2), 131–137. https://doi.org/10.1109/MCOM.2016.7402272
  • Heydarpour, F., Abbasi, E., Ebadi, M., & Karbassi, S.-M. (2020). Solving an optimal control problem of cancer treatment by artificial neural networks. International Journal of Interactive Multimedia & Artificial Intelligence, 6(4), 18–25. https://doi.org/10.9781/ijimai.2020.11.011
  • Hu, P., Dhelim, S., Ning, H., & Qiu, T. (2017). Survey on fog computing: Architecture, key technologies, applications and open issues. Journal of Network and Computer Applications, 98, 27–42. https://doi.org/10.1016/j.jnca.2017.09.002
  • Jafari, H., Malinowski, M. T., & Egbadi, M. (2021). Existence of chaos for partial difference equations via tangent and cotangent functions. Advances in Difference Equations, 2021(1), 1–17. doi:10.1186/s13662-020-03162-2
  • Kaur, M., & Aron, R. (2020). Energy-aware load balancing in fog cloud computing. Materials Today: Proceedings, 1–5. https://doi.org/10.1016/j.matpr.2020.11.121
  • Ko, H., Pack, S., & Leung, V. C. (2019). Coverage-guaranteed and energy-efficient participant selection strategy in mobile crowdsensing. IEEE Internet of Things Journal, 6(2), 3202–3211. https://doi.org/10.1109/JIOT.2018.2880463
  • Kumar, A. N., Sanjay, C., & Chakravarthy, M. (2020). Mamdani fuzzy expert system based directional relaying approach for Six-phase transmission line. Int. J. Interact. Multim. Artif. Intell, 6(1), 41–50. https://doi.org/10.9781/ijimai.2019.06.002
  • Li, T., Liu, A., & Huang, C. (2016). A similarity scenario-based recommendation model with small disturbances for unknown items in social networks. IEEE Access, 4, 9251–9272. https://doi.org/10.1109/ACCESS.2016.2647236
  • Li, T., Liu, Y., Gao, L., & Liu, A. (2017). A cooperative-based model for smart-sensing tasks in fog computing. IEEE Access, 5, 21296–21311. https://doi.org/10.1109/ACCESS.2017.2756826
  • Luceri, L., Cardoso, F., Papandrea, M., Giordano, S., Buwaya, J., Kundig, S., Angelopoulos, C. M., Rolim, J., Zhao, Z., Carrera, J. L., & Braun, T. (2018). Vivo: A secure, privacy-preserving, and real-time crowd-sensing framework for the Internet of things. Pervasive and Mobile Computing, 49, 126–138. https://doi.org/10.1016/j.pmcj.2018.07.003
  • Luo, T., Huang, J., Kanhere, S. S., Zhang, J., & Das, S. K. (2019). Improving IoT data quality in mobile crowd sensing: A cross validation approach. IEEE Internet of Things Journal, 6(3), 5651–5664. https://doi.org/10.1109/JIOT.2019.2904704
  • Neshat, M. (2013). Faipso: Fuzzy adaptive informed particle swarm optimization. Neural Computing and Applications, 23(1), 95–116. https://doi.org/10.1007/s00521-012-1256-z
  • Rezk, H., Arfaoui, J., & Gomaa, M. R. (2021). Optimal parameter estimation of solar PV panel based on hybrid particle swarm and grey wolf optimization algorithms. International Journal of Interactive Multimedia & Artificial Intelligence, 6(6), 1–11. https://doi.org/10.9781/ijimai.2020.12.001
  • Song, S., Liu, Z., Li, Z., Xing, T., & Fang, D. (2020). Coverage-oriented task assignment for mobile crowdsensing. IEEE Internet of Things Journal, 7(8), 7407–7418. https://doi.org/10.1109/JIOT.2020.2984826
  • Tharwat, A., & Hassanien, A. E. (2018). Chaotic antlion algorithm for parameter optimization of support vector machine. Applied Intelligence, 48(3), 670–686. https://doi.org/10.1007/s10489-017-0994-0
  • Wang, J., Hu, C., & Liu, A. (2017). Comprehensive optimization of energy consumption and delay performance for green communication in Internet of things. Mobile Information Systems, 2017, 1–17, Article ID: 3206160. https://doi.org/10.1155/2017/3206160
  • Wang, J., Tang, J., Xue, G., & Yang, D. (2017). Towards energy-efficient task scheduling on smartphones in mobile crowd sensing systems. Computer Networks, 115, 100–109. https://doi.org/10.1016/j.comnet.2016.11.020
  • Wang, J., Wang, L., Wang, Y., Zhang, D., & Kong, L. (2018). Task allocation in mobile crowd sensing: State-of-the-art and future opportunities. IEEE Internet of Things Journal, 5(5), 3747–3757. https://doi.org/10.1109/JIOT.2018.2864341
  • Wang, L., Yu, Z., Guo, B., Yi, F., & Xiong, F. (2018). Mobile crowd sensing task optimal allocation: A mobility pattern matching perspective. Frontiers of Computer Science, 12(2), 231–244. https://doi.org/10.1007/s11704-017-7024-6
  • Wang, X., Ning, Z., Hu, X., Ngai, E. C. H., Wang, L., Hu, B., & Kwok, R. Y. (2018). A city-wide real-time traffic management system: Enabling crowdsensing in social Internet of vehicles. IEEE Communications Magazine, 56(9), 19–25. https://doi.org/10.1109/MCOM.2018.1701065
  • Xiong, H., Zhang, D., Chen, G., Wang, L., & Gauthier, V. (2015). Crowdtasker: Maximizing coverage quality in piggyback crowdsensing under budget constraint. IEEE International Conference on Pervasive computing and Communications (PerCom), pp. 55-62.
  • Xiong, H., Zhang, D., Wang, L., Gibson, J. P., & Zhu, J. (2015). EEMC. ACM Transactions on Intelligent Systems and Technology, 6(3), 1–26. https://doi.org/10.1145/2644827
  • Yaghmazadeh, O., Cicoira, F., Bernards, D. A., Yang, S. Y., Bonnassieux, Y., & Malliaras, G. G. (2011). Optimization of organic electrochemical transistors for sensor applications. Journal of Polymer Science Part B: Polymer Physics, 49(1), 34–39. https://doi.org/10.1002/polb.22129
  • Yu, J., Xiao, M., Gao, G., & Hu, C. (2016). Minimum cost spatial-temporal task allocation in mobile crowdsensing. International Conference on wireless algorithms, systems, and applications.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.