2023-01-29
SVD Compression and Energy Harvesting Based Energy Efficient 3D-MI-UWSNs
By
Progress In Electromagnetics Research Letters, Vol. 109, 15-22, 2023
Abstract
In underwater wireless sensor networks (UWSNs), the limited availability and non-rechargeability of sensor node batteries necessitated the advancement of energy optimization techniques. Optimal clustering is one such technique that reduces the energy consumption of the networks. In this letter, we propose optimal cluster compression technique jointly with energy harvesting. In optimal clustering compression, we perform optimal clustering of networks with singular value decomposition (SVD) as compression technique to reduce the redundant data generated at the cluster heads (CHs). Besides, adopting energy harvesting technique, node batteries are periodically recharged. The performance of the proposed model is evaluated in terms of network lifetime and throughput.
Citation
Sadanand Yadav, and Vinay Kumar, "SVD Compression and Energy Harvesting Based Energy Efficient 3D-MI-UWSNs ," Progress In Electromagnetics Research Letters, Vol. 109, 15-22, 2023.
doi:10.2528/PIERL22120219
References

1. Akyildiz, I. F., P. Wang, and Z. Sun, "Realizing underwater communication through magnetic induction," IEEE Communications Magazine, Vol. 53, No. 11, 42-48, 2015.
doi:10.1109/MCOM.2015.7321970        Google Scholar

2. Sharma, A. K., S. Yadav, S. N. Dandu, V. Kumar, and J. Sengupta, "Magnetic induction-based non-conventional media communications: A review," IEEE Sensors Journal, Vol. 17, No. 4, 926-940, 2016.        Google Scholar

3. Yadav, S., V. Kumar, S. B. Dhok, and D. N. K. Jayakody, "Energy-efficient design of MI communication-based 3-D non-conventional WSNs," IEEE Systems Journal, Vol. 14, No. 2, 2585-2588, 2019.
doi:10.1109/JSYST.2019.2918184        Google Scholar

4. Kumar, V., S. Yadav, A. Sharma, A. Prakash, R. Tripathi, and D. N. K. Jayakody, "3D-multilayer magneto-inductive transceiver coil structure and optimal placement of relays for non-conventional media," Wireless Networks, Vol. 28, 2115-2129, Springer, 2022.
doi:10.1007/s11276-022-02949-3        Google Scholar

5. Liu, Y., S. Gong, Q. Liu, and M. Hou, "A mechanical transmitter for undersea magnetic induction communication," IEEE Transactions on Antennas and Propagation, Vol. 69, 6391-6400, 2022.        Google Scholar

6. Kumar, V., R. Bhusari, S. B. Dhok, A. Prakash, R. Tripathi, and S. Tiwari, "Design of magnetic induction based energy-efficient WSNs for non-conventional media using multi-layer transmitter-enabled novel energy model," IEEE Systems Journal, Vol. 13, No. 2, 1285-1296, 2018.
doi:10.1109/JSYST.2018.2852487        Google Scholar

7. Gulbahar, B. and O. B. Akan, "A communication theoretical modeling and analysis of underwater magneto-inductive wireless channels," IEEE Transactions on Wireless Communications, Vol. 11, No. 9, 3326-3334, 2012.
doi:10.1109/TWC.2012.070912.111943        Google Scholar

8. Sun, Z. and I. F. Akyildiz, "Magnetic induction communications for wireless underground sensor networks," IEEE Transactions on Antennas and Propagation, Vol. 58, No. 7, 2426-2435, 2010.
doi:10.1109/TAP.2010.2048858        Google Scholar

9. Paek, J. and J. Ko, "K-means clustering-based data compression scheme for wireless imaging sensor networks," IEEE Systems Journal, Vol. 11, No. 4, 2652-2662, 2015.
doi:10.1109/JSYST.2015.2491359        Google Scholar

10. Wang, S., T. L. N. Nguyen, and Y. Shin, "Data collection strategy for magnetic induction based monitoring in underwater sensor networks," IEEE Access, Vol. 6, 43644-43653, 2018.
doi:10.1109/ACCESS.2018.2861946        Google Scholar

11. Ghoreyshi, S. M., A. Shahrabi, T. Boutaleb, and M. Khalily, "Mobile data gathering with hop-constrained clustering in underwater sensor networks," IEEE Access, Vol. 7, 21118-21132, 2019.
doi:10.1109/ACCESS.2019.2897872        Google Scholar

12. Rufai, A. M., G. Anbarjafari, and H. Demirel, "Lossy image compression using singular value decomposition and wavelet difference reduction," Digital Signal Processing, Vol. 24, 117-123, Elsevier, 2014.        Google Scholar

13. Amini, N., A. Vahdatpour, W. Xu, and M. Gerla, "Cluster size optimization in sensor networks with decentralized cluster-based protocols," Computer Communications, Vol. 35, 207-220, Elsevier, 2012.        Google Scholar

14. Vermaak, H. J., K. Kusakana, and S. P. Koko, "Status of micro-hydro-kinetic river technology in rural applications: A review of literature," Renewable and Sustainable Energy Reviews, Vol. 29, 625-633, Elsevier, 2014.        Google Scholar

15. Pobering, S. and N. Schwesinger, "A novel hydropower harvesting device," 2004 International Conference on MEMS, NANO and Smart Systems (ICMENS'04), 480-485, IEEE, 2004.
doi:10.1109/ICMENS.2004.1508997        Google Scholar