Abstract
Wireless sensor network (WSN) has now become a newfangled area of research. WSN is an interconnection of sensor nodes which are installed in a region for a particular task. Sensors sense their surrounding physical attributes and transmit the acquired information to the dedicated node or base station. There are some challenges associated with WSN: Energy efficiency, security, coverage, connectivity, responsiveness, etc. WSN has large number of application areas. Energy efficiency of the network is a major concern for some applications because battery replacement is not easy. Clustering is used to enhance energy efficiency of the network. When sensor nodes transmit information, some amount of energy dissipated. But when nodes are not in transmitting state, still some amount of energy is consumed in listening to data. In this paper, we proposed a hybrid of probabilistic and Sleep–wakeup clusterings to decrease the energy consumption due to idle listening. The proposed method adds the energy efficiency by using adaptive probabilistic approach with a sleep–wakeup schedule. Results are simulated in MATLAB. The analysis of results reveals that the duration of first-node dead and last-node dead while considering round number is increased in comparison of LEACH, which ultimately shows increased energy efficiency of the system.
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Kulshrestha, R., Ramani, P., Sharma, A.K. (2020). A Hybrid of Scheduling and Probabilistic Approach to Decrease the Effect of Idle Listening in WSN. In: Peng, SL., Son, L.H., Suseendran, G., Balaganesh, D. (eds) Intelligent Computing and Innovation on Data Science. Lecture Notes in Networks and Systems, vol 118. Springer, Singapore. https://doi.org/10.1007/978-981-15-3284-9_27
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DOI: https://doi.org/10.1007/978-981-15-3284-9_27
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