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A task-based model for minimizing energy consumption in WSNs

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Abstract

Hardware viewed in current energy models, but no appropriate attention is given to the network environment and parameters. Components of the traditional design of the network are often viewed individually and separately in terms of power consumption. In this paper we, look at all possible sensor operations and generate a model for energy management in its integrated network. The work proposed divides these tasks into five energy consuming parts. The sensor’s energy consumption is then modeled on its energy-consuming parts, parameters, and input operations. Thus, the energy consumption of the sensor can be decreased by effectively balancing and performing the chores of its constituents. The suggested strategy improves energy efficiency and can also be used as guide in setting wireless sensor networks (WSNs) parameters. Further more, It can help in designing an energy efficient WSNs. The serious energy limitations, however, pose special challenges for WSNs applications to establish and project scheduling which is usually has a strong influence on achieving energy efficiency and usage. This paper provides a framework for preparing the tasks, in which each node decides to do next according to the observed portion of the request. Within this Framework, we can exchange the application efficiency and the energy consumption provided by a weighted reward function and thus obtain better results in terms of energy/ performance. We can further improve this energy/performance trade off by exchanging data between neighboring nodes. The suggested approach analyzed in a target monitoring program. The simulation experiments show that cooperative approaches for this type of application are superior to non-cooperative approaches.

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Acknowledgements

The authors would like to thank Al-Balqa Applied University for its continuous support and encouragement.

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Correspondence to Jafar A. Alzubi.

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Alrabea, A., Alzubi, O.A. & Alzubi, J.A. A task-based model for minimizing energy consumption in WSNs. Energy Syst 13, 671–688 (2022). https://doi.org/10.1007/s12667-019-00372-w

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