In recent years, wireless sensor networks (WSN) have gotten a lot of attention. As a result, a number of power-aware algorithms using a variety of techniques have been created. Time scheduling methodologies, delay bound constraints, data adoption strategies, data aggregation, mobility sinks, a query-based approach, and management of spare nodes based on residual energy levels are all used in these tactics. The lifetime extensions gained through practical deployments are much smaller than those obtained using equivalent approaches in simulations. In relation to the load, the battery's rate capacity and recovery impact are investigated. Three key causes of battery mortality have been identified: poor sample interval selection, the effect of the sensor field's environment, and transferring the detected data with an improper transmission power level. Using a realistic method, the impact of altering transmission power levels on the lifetime of the sensor node and hence the wireless sensor network is explored in this research. During the procedure, an ideal value for data packet transmission power is identified, lowering the battery's Rate Capacity. The sensor node's lifetime was enhanced by about 23% with the optimised transmission power level. The goal of this project in the future is to employ the best sampling interval and transmission power level to extend the WSN's lifetime even further.
Author(S) Details
Satyanarayana Chanagala
SBIT, Khammam, Telangana, India.
M. Srinivasa Sesha Sai
KKR & KSR Institute of Technology and Sciences, Guntur (A.P), India.
K. Madhu Sudhana Rao
KKR & KSR Institute of Technology and Sciences, Guntur (A.P), India.
Neelima Pravin Dudhe
Rajiv Gandhi College of Engineering, Research, and Technology, Chandrapur (MH), India.
M. Kavitha
MNR College of College of Engineering and Technology, Sangareddy, India.
View Book:- https://stm.bookpi.org/NPER-V9/article/view/6293
No comments:
Post a Comment