Enlightening Network Lifetime based on Dynamic Time Orient Energy Optimization in Wireless Sensor Network

Main Article Content

S. Priya
P. Suganthi

Abstract

Mobile Ad-hoc Networks (MANET) are a set of Large-scale infrastructure and mobile device networks that build themselves without centralized control to provide various services through mobile. However, the quality of service of MANET is highly dependent on multiple parameters. Many routing schemes in literature use hop count, mobility speed, direction, etc. Similarly, the flow-based approach chooses long routes, which increases latency and reduces throughput efficiency. However, not all methods work well with all Quality of Service (QoS) parameters. To introduce a Dynamic Time Orient Energy Optimization (DTOEO) algorithm to construct the energy-based tree formation to achieve the minimum energy consumption network. Energy-based Dynamic Tree Routing to provide higher energy node and shortest route estimation that help to better transmission quality. In this proposed DTOEO method, perform three stages, there are i). Source node discovery process, ii). Time-orient density estimation, and iii). Energy-based Dynamic Tree Routing. In this stage, orient density estimation evaluates the data transmission size for each window period. To assess the consuming energy in the overall network. The proposed method of performance evaluation using various QoS matrices and its comparison to the existing process provides better performance.

Article Details

How to Cite
Priya, S. ., & Suganthi, P. . (2023). Enlightening Network Lifetime based on Dynamic Time Orient Energy Optimization in Wireless Sensor Network. International Journal on Recent and Innovation Trends in Computing and Communication, 11(4s), 149–155. https://doi.org/10.17762/ijritcc.v11i4s.6321
Section
Articles

References

H. Azarhava, and J. Musevi Niya, "Energy Efficient Resource Allocation in Wireless Energy Harvesting Sensor Networks," in IEEE Wireless Communications Letters, vol. 9, no. 7, July 2020, pp. 1000-1003, doi: 10.1109/LWC.2020.2978049.

M. Song, and M. Zheng, "Energy Efficiency Optimization For Wireless Powered Sensor Networks With Nonorthogonal Multiple Access," in IEEE Sensors Letters, vol. 2, no. 1, March 2018, pp. 1-4, Art no. 7500304, doi: 10.1109/LSENS.2018.2792454.

N. Aslam, K. Xia, and M. Hadi, "Optimal Wireless Charging Inclusive of Intellectual Routing Based on SARSA Learning in Renewable Wireless Sensor Networks," in IEEE Sensors Journal, vol. 19, no. 18, Sept.15, 2019 pp. 8340-8351, 15 doi: 10.1109/JSEN.2019.2918865.

G. Li, S. Peng, C. Wang, J. Niu, and Y. Yuan, "An energy-efficient data collection scheme using denoising autoencoder in wireless sensor networks," in Tsinghua Science and Technology, vol. 24, no. 1, Feb. 2019, pp. 86-96, DOI: 10.26599/TST.2018.9010002.

S. He, K. Xie, W. Chen, D. Zhang, and J. Wen, "Energy-Aware Routing for SWIPT in Multi-Hop Energy-Constrained Wireless Network," in IEEE Access, vol. 6, 2018, pp. 17996-18008, doi: 10.1109/ACCESS.2018.2820093.

P. Mekikis, E. Kartsakli, A. Antonopoulos, L. Alonso, and C. Verikoukis, "Connectivity Analysis in Clustered Wireless Sensor Networks Powered by Solar Energy," in IEEE Transactions on Wireless Communications, vol. 17, no. 4, April 2018, pp. 2389-2401, doi: 10.1109/TWC.2018.2794963.

S. Guo, Y. Shi, Y. Yang, and B. Xiao, "Energy Efficiency Maximization in Mobile Wireless Energy Harvesting Sensor Networks," in IEEE Transactions on Mobile Computing, vol. 17, no. 7, 1 July 2018, pp. 1524-1537, doi: 10.1109/TMC.2017.2773067.

O. Amjad, E. Bedeer, and S. Ikki, "Energy-Efficiency Maximization of Self-Sustained Wireless Body Area Sensor Networks," in IEEE Sensors Letters, vol. 3, no. 12, Dec. 2019, pp. 1-4, Art no. 7501204, doi: 10.1109/LSENS.2019.2946851.

L. Hung, F. Leu, K. Tsai, and C. Ko, "Energy-Efficient Cooperative Routing Scheme for Heterogeneous Wireless Sensor Networks," in IEEE Access, vol. 8, 2020, pp. 56321-56332, doi: 10.1109/ACCESS.2020.2980877.

D. Sharma, and A. Bhondekar, "Traffic and Energy Aware Routing for Heterogeneous Wireless Sensor Networks," in IEEE Communications Letters, vol. 22, no. 8, Aug. 2018, pp. 1608-1611, doi: 10.1109/LCOMM.2018.2841911.

N. Saeed, A. Celik, T. Al-Naffouri and M. Alouini, "Localization of Energy Harvesting Empowered Underwater Optical Wireless Sensor Networks," in IEEE Transactions on Wireless Communications, vol. 18, no. 5, May 2019, pp. 2652-2663, doi: 10.1109/TWC.2019.2906309.

J. Geoffrine, and V. Geetha, "Energy Optimization With Higher Information Quality for SHM Application in Wireless Sensor Networks," in IEEE Sensors Journal, vol. 19, no. 9, 1 May 1, 2019, pp. 3513-3520, doi: 10.1109/JSEN.2019.2892870.

V. Gupta, and S. De, "Collaborative Multi-Sensing in Energy Harvesting Wireless Sensor Networks," in IEEE Transactions on Signal and Information Processing over Networks, vol. 6, 2020, pp. 426-441, doi: 10.1109/TSIPN.2020.2995502.

S. Gupta and N. Mehta, "Revisiting Effectiveness of Energy Conserving Opportunistic Transmission Schemes in Energy Harvesting Wireless Sensor Networks," in IEEE Transactions on Communications, vol. 67, no. 4, April 2019, pp. 2968-2980,doi: 10.1109/TCOMM.2018.2889331.

H. Ayadi, A. Zouinkhi, T. Val, A. van den Bossche and M. Abdelkrim, "Network Lifetime Management in Wireless Sensor Networks," in IEEE Sensors Journal, vol. 18, no. 15, Aug.1, 2018, pp. 6438-6445, doi: 10.1109/JSEN.2018.2840830.

M. Khan et al., "Improving Energy Efficiency With Content-Based Adaptive and Dynamic Scheduling in Wireless Sensor Networks," in IEEE Access, vol. 8, 2020, pp. 176495-176520, doi: 10.1109/ACCESS.2020.3026939.

C. Albea Sanchez, O. Mokrenko, L. Zaccarian and S. Lesecq, "A Hybrid Control Law for Energy-Oriented Tasks Scheduling in Wireless Sensor Networks," in IEEE Transactions on Control Systems Technology, vol. 26, no. 6, Nov. 2018, pp. 1995-2007, doi: 10.1109/TCST.2017.2750999.

Y. Zhang, X. Zhang, S. Ning, J. Gao and Y. Liu, "Energy-Efficient Multilevel Heterogeneous Routing Protocol for Wireless Sensor Networks," in IEEE Access, vol. 7, 2019, pp. 55873-55884, doi: 10.1109/ACCESS.2019.2900742.