PROJECT TITLE :

CDPM A Combinational Data Prediction Model for Data Transmission Reduction in WSN

ABSTRACT:

In wireless sensor networks (WSN), data prediction methods have recently emerged as a significant way to reduce the amount of redundant data transfers and in extending the overall lifetime of the network. There are currently two distinct categories of data prediction algorithms in use. The first approach concentrated on piecing together historical data and developing retrospective models, which led to delays that were unmanageable. The second model addresses the problem of data forecasting for the future and provides forward models, which call for an increase in data transmissions. Method: In this section, we developed a Combinational Data Prediction Model (CDPM) that can both build prior data in order to control delays and anticipate future data in order to reduce the transmission of an excessive amount of data. Two different algorithms are implemented in order to put this paradigm into practice in WSN applications. The first algorithm constructs optimal models for sensor nodes in a step-by-step manner (SNs). The other one forecasts and recalculates the readings based on the data that is sensed by the base stations (BS). Comparison: In order to evaluate the efficacy of the CDPM data-prediction method that we have proposed, a WSN-based real application that makes use of real data is modeled through simulation. The effectiveness of CDPM is evaluated alongside that of HLMS, ELR, and P-PDA algorithms, respectively. Results: When compared with HLMS, ELR, and P-PDA algorithms, respectively, the CDPM model showed significant transmission suppression (16.49%, 19.51%, and 20.57%%), reduced energy consumption (29.56%, 50.14%, 61.12%), and improved accuracy (15.38%, 21.42%, 31.25%). The delay that is brought on by CDPM training can also be managed through the data collection process. Concluding remarks: The findings indicated that the proposed CDPM was more effective than a single forward or backward model in terms of reduced data transmission, improved energy efficiency, and regulated latency.