An Energy Efficient Weighted Clustering Scheme with Packet Service Time in Multimedia Data Transmission in WMSN
Keywords:
Wireless Multimedia Sensor Network, Clustering, QoS, weighted factor, routing, PSTAbstract
Wireless multimedia sensor Network (WMSN) are formulated with the deployed sensor devices within specified location aimed to monitor the target. With the target information multimedia data were generated in the form of audio, video or image. The multimedia data were stored in the devices of the sensor to achieve the higher storage capacity. Upon the effective sensing of the multimedida information for the transmission between the source to destination node the effective routes are identified with the intermediate nodes. However, the comparison the scalar data handling multimedia data is complex to achieve the effective multimedia communication in the WMSN. In the multimedia data environment the challenges associated with the scenario are routing and data delivery. To achieve the effective network performance in WMSN sensor nodes need to be optimized for the route establishment. In order to efficiently transmit multimedia data in a multimedia setting, the clustering method was presented in this study. The proposed model is defined as the Efficient Weighted Communication Protocol (EWHCP) model for the optimal route selection and data transmission to increased the QoS with the reduced end-to-end delay. The proposed EWHCP method implements energy aware admission control among the sensor nodes to achieve efficient utilization of resources for data transmission. After that, the measure of packet service time and channel utilization is carried out for all sensor nodes in the network to select the next forwarding node through which the data is transmitted. QoS aware routing is performed with the help of neighbor node’s weight factor. Therefore, the proposed EWHCP attains minimum delay for multimedia content to reach the destination sink node from source sensor node. Based on the obtained experimental results, the suggested EWHCP approach is able to select an efficient route for multimedia data transmission by taking into account the average Packet Service Time (PST), channel utilization, and minimal hop count.
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Li, S., Kim, J. G., Han, D. H., & Lee, K. S. (2019). A survey of energy-efficient communication protocols with QoS guarantees in wireless multimedia sensor networks. Sensors, 19(1), 199.
Alqaralleh, B. A., Mohanty, S. N., Gupta, D., Khanna, A., Shankar, K., & Vaiyapuri, T. (2020). Reliable multi-object tracking model using deep learning and energy efficient wireless multimedia sensor networks. IEEE Access, 8, 213426-213436.
Wang, D., Liu, J., Yao, D., & Member, I. E. E. E. (2020). An energy-efficient distributed adaptive cooperative routing based on reinforcement learning in wireless multimedia sensor networks. Computer Networks, 178, 107313.
Khattak, H. A., Ameer, Z., Din, U. I., & Khan, M. K. (2019). Cross-layer design and optimization techniques in wireless multimedia sensor networks for smart cities. Computer Science and Information Systems, 16(1), 1-17.
Bernard, M. S., Pei, T., & Nasser, K. (2019). QoS strategies for wireless multimedia sensor networks in the context of IoT at the MAC layer, application layer, and cross-layer algorithms. Journal of Computer Networks and Communications, 2019.
Yazici, A., Koyuncu, M., Sert, S. A., & Yilmaz, T. (2019). A fusion-based framework for wireless multimedia sensor networks in surveillance applications. IEEE Access, 7, 88418-88434.
Genta, A., Lobiyal, D. K., & Abawajy, J. H. (2019). Energy efficient multipath routing algorithm for wireless multimedia sensor network. Sensors, 19(17), 3642.
García, S., Larios, D. F., Barbancho, J., Personal, E., Mora-Merchán, J. M., & León, C. (2019). Heterogeneous LoRa-based wireless multimedia sensor network multiprocessor platform for environmental monitoring. Sensors, 19(16), 3446.
Trinh, B. N., Murphy, L., & Muntean, G. M. (2020). A reinforcement learning-based duty cycle adjustment technique in wireless multimedia sensor networks. IEEE Access, 8, 58774-58787.
Jiao, Z., Zhang, L., Xu, M., Cai, C., & Xiong, J. (2019). Coverage control algorithm-based adaptive particle swarm optimization and node sleeping in wireless multimedia sensor networks. IEEE Access, 7, 170096-170105.
Küçükkeçeci, C., & Yazici, A. (2019). Multilevel object tracking in wireless multimedia sensor networks for surveillance applications using graph-based big data. IEEE Access, 7, 67818-67832.
Bhanu, K. N., Reddy, T. B., & Hanumanthappa, M. (2019). Multi-agent based context aware information gathering for agriculture using Wireless Multimedia Sensor Networks. Egyptian Informatics Journal, 20(1), 33-44.
Janarthanan, A., & Kumar, D. (2019). Localization based evolutionary routing (LOBER) for efficient aggregation in wireless multimedia sensor networks. Computers, Materials & Continua, 60(3), 895-912.
Aswale, S., & Ghorpade, V. R. (2021). Geographic multipath routing based on triangle link quality metric with minimum inter-path interference for wireless multimedia sensor networks. Journal of King Saud University-Computer and Information Sciences, 33(1), 33-44.
Hussein, W. A., Ali, B. M., Rasid, M. F. A., & Hashim, F. (2022). Smart geographical routing protocol achieving high QoS and energy efficiency based for wireless multimedia sensor networks. Egyptian Informatics Journal.
Alqahtani, A. S. (2021). Improve the QoS using multi-path routing protocol for Wireless Multimedia Sensor Network. Environmental Technology & Innovation, 24, 101850.
Feng, S., Shen, S., Huang, L., Champion, A. C., Yu, S., Wu, C., & Zhang, Y. (2019). Three-dimensional robot localization using cameras in wireless multimedia sensor networks. Journal of Network and Computer Applications, 146, 102425.
Wang, D., Liu, J., Yao, D., & Member, I. E. E. E. (2020). An energy-efficient distributed adaptive cooperative routing based on reinforcement learning in wireless multimedia sensor networks. Computer Networks, 178, 107313.
Tekin, N., & Gungor, V. C. (2020). Analysis of compressive sensing and energy harvesting for wireless multimedia sensor networks. Ad Hoc Networks, 103, 102164.
Xiao, D., Li, M., Wang, M., Liang, J., & Liu, R. (2020). Low-cost and high-efficiency privacy-protection scheme for distributed compressive video sensing in wireless multimedia sensor networks. Journal of Network and Computer Applications, 161, 102654.
Jemili, I., Ghrab, D., Belghith, A., & Mosbah, M. (2020). Cross-layer adaptive multipath routing for multimedia wireless sensor networks under duty cycle mode. Ad Hoc Networks, 109, 102292.
Merwe, M. van der, Petrova, M., Jovanović, A., Santos, M., & Rodríguez, M. Text Summarization using Transformer-based Models. Kuwait Journal of Machine Learning, 1(3). Retrieved from http://kuwaitjournals.com/index.php/kjml/article/view/141
Meena , B. S. . (2023). Plant Health Prediction and Monitoring Based on convolution Neural Network in North-East India. International Journal on Recent and Innovation Trends in Computing and Communication, 11(2s), 12–19. https://doi.org/10.17762/ijritcc.v11i2s.6024
Anupong, W., Azhagumurugan, R., Sahay, K.B., Dhabliya, D., Kumar, R., Vijendra Babu, D. Towards a high precision in AMI-based smart meters and new technologies in the smart grid (2022) Sustainable Computing: Informatics and Systems, 35, art. no. 100690,
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