Deep Learning-based Prioritized Packet Classification and Optimal Route Selection in Wireless Multimedia Sensor Networks

REFERENCES

• Y. Ur Rehman, M. Tariq, and T. Sato, “A novel energy efficient object detection and image transmission approach for wireless multimedia sensor networks,” IEEE Sensors J., Vol. 16, no. 15, pp. 5942–5949, Jun. 2016.
   Web of Science ®Google Scholar
• S. Hengstler, D. Prashanth, S. Fong, and H. Aghajan. “Mesh eye: a hybrid resolution smart camera mote for applications in distributed intelligent surveillance”, in Proceedings of the 6th International Conference on Information Processing in Sensor Networks, Cambridge Massachusetts USA, Apr. 2007, pp. 360–9.
   Google Scholar
• S. Chen, Z. Yuan, and G.-M. Muntean, “An energy-aware routing algorithm for quality-oriented wireless video delivery,” IEEE Trans. Broadcast., Vol. 62, no. 1, pp. 55–68, 2016.
   Web of Science ®Google Scholar
• A. Chikh, and M. Lehsaini, “Multipath routing protocols for wireless multimedia sensor networks: a survey,” Int. J. Commun. Networks Distrib. Syst., Vol. 20, no. 1, pp. 60–81, 2017.
   Web of Science ®Google Scholar
• N. Magaia, N. Horta, R. Neves, P. R. Pereira, and M. Correia, “A multi-objective routing algorithm for wireless multimedia sensor networks,” Appl. Soft. Comput., Vol. 30, pp. 104–12, 2015.
   Web of Science ®Google Scholar
• M. Civelek, and A. Yazici, “Automated moving object classification in wireless multimedia sensor networks,” IEEE Sensors J., Vol. 17, no. 4, pp. 1116–31, 15 Feb. 2017.
   Web of Science ®Google Scholar
• A. Arar, A. Mohamed, A. A. El-Sherif, and V. C. Leung, “Optimal resource allocation for green and clustered video sensor networks,” IEEE Syst. J., Vol. 12, no. 3, pp. 2117–28, 2017.
   Web of Science ®Google Scholar
• H. Shen, and G. Bai, “Routing in wireless multimedia sensor networks: a survey and challenges ahead,” J. Netw. Comput. Appl., Vol. 71, pp. 30–49, 2016.
   Web of Science ®Google Scholar
• O. Deepa, and N. Karthikeyani Visalakshi, “A self-optimized QoS aware RED-ACO routing protocols for wireless sensor networks,” Middle East J. Sci. Res., Vol. 24, pp. 224–30, Mar. 2016.
   Google Scholar
• M. Z. Hasan, F. Al-Turjman, and H. Al-Rizzo, “Optimized multi-constrained quality-of-service multipath routing approach for multimedia sensor networks,” IEEE Sensors J., Vol. 17, no. 7, pp. 2298–309, 2017.
   Web of Science ®Google Scholar
• L. Zhou, D. Wu, Z. Dong, and X. Li, “When collaboration hugs intelligence: content delivery over ultra-dense networks,” IEEE Commun. Mag., Vol. 55, no. 12, pp. 91–5, 2017.
   Web of Science ®Google Scholar
• Z. Lin, G. Li, and J. Li, “Cross-layer energy optimization in cooperative MISO wireless sensor networks,” Comput. Commun., Vol. 157, pp. 351–60, 2020.
   Web of Science ®Google Scholar
• S. Aswale, and V. R. Ghorpade, “Survey of QoS routing protocols in wireless multimedia sensor networks,” J. Comput. Networks Commun., 1–29, 2015.
   Google Scholar
• R. Chiwariro, and N. Thangadurai, “Quality of service aware routing protocols in wireless multimedia sensor networks: survey,” Int. J. Inf. Technol., 2020. DOI: 10.1007/s41870-020-00478-w.
   Google Scholar
• O. Deepa, and J. Suguna, “An optimized QoS-based clustering with multipath routing protocol for wireless sensor networks,” Comput. Inf. Sci., Vol. 32, no. 7, pp. 763–74, Dec. 2017.
   Google Scholar
• R. Ranjan, and S. Varma, “Challenges and implementation on cross-layer design for wireless sensor networks,” Wirel. Pers. Commun., Vol. 86, no. 2, pp. 1037–60, 2016.
   Web of Science ®Google Scholar
• Y.-L. Chen, and H.-P. Lai, “Priority-based transmission rate control with a fuzzy logical controller in wireless multimedia sensor networks,” Comput. Math. Appl., Vol. 64, no. 5, pp. 688–98, Sept. 2012.
   Web of Science ®Google Scholar
• I. B. Bouazzi, and M. Jamila Atri. Priority-Based Queuing and Transmission Rate Management using a Fuzzy Logic Controller in WSNs. ICT Express, Elsevier, 2017.
   Google Scholar
• S. Aswale, and V. R. Ghorpade, “Geographic multipath routing based on triangle link quality metric with minimum inter-path interference for wireless multimedia sensor networks,” Comput. Inf. Sci., Vol. 33, no. 1, pp. 33–44, Jan. 2021.
   Google Scholar
• N. Khernane, J.-F. Couchot, and A. Mostefaoui, “Maximum network lifetime with optimal power/rate and routing trade-off for wireless multimedia sensor networks,” Comput. Commun., Vol. 124, pp. 1–16, 2018.
   Web of Science ®Google Scholar
• L. Cobo, A. Quintero, and S. Pierre, “Ant-based routing for wireless multimedia sensor networks using multiple QoS metrics,” Comput. Netw., Vol. 54, no. 17, pp. 2991–3010, 2010.
   Web of Science ®Google Scholar
• S. Basak, and T. Acharya, “Cross-layer optimization for outage minimizing routing in cognitive radio ad hoc networks with primary users’ outage protection,” J. Netw. Comput. Appl., Vol. 98, pp. 114–24, Nov. 2017.
   Web of Science ®Google Scholar
• T. Mekonnen, P. Porambage, E. Harjula, and M. Ylianttila, “Energy consumption analysis of high-quality multi-tier wireless multimedia sensor network,” IEEE. Access., Vol. 5, pp. 15848–58, 2017.
   Web of Science ®Google Scholar
• N. Khernane, J.-F. Couchot, and A. Mostefaoui, “Optimal power/rate trade-off for the internet of multimedia things lifetime maximization under dynamic links capacity,” Future Gener. Comput. Syst., Vol. 93, pp. 737–50, 2019.
   Web of Science ®Google Scholar
• D. Binu, and B. S. Kariyappa, “RideNN: a new rider optimization algorithm-based neural network for fault diagnosis in analog circuits,” IEEE Trans. Instrum. Meas., Vol. 68, no. 1, pp. 2–26, 2019.
   Web of Science ®Google Scholar
• S. Arora, and S. Singh, “Butterfly optimization algorithm: a novel approach for global optimization,” Soft. Comput., Vol. 23, pp. 715–34, Mar. 2018.
   Web of Science ®Google Scholar
• Ministry of Science, Technology and Innovation (MinCiencias), Dr. Adrian, Universidad Del Cauca, Popayán, Colombia. “Labeled Network Traffic flows - 141 Applications,” Kaggle, Accessed 25 January 2020.
   Google Scholar
• M. Marsaline Beno, I. R. Valarmathi, S. M. Swamy, and B. R. Rajakumar, “Threshold prediction for segmenting tumour from brain MRI scans,” Int. J. Imag. Syst. Technol., Vol. 24, no. 2, pp. 129–37, 2014.
   Web of Science ®Google Scholar