Abstract
Active participation of clustered nodes in a static Wireless Sensor Network offers comprehensive relief to the perennial arising out of limited energy reserve. In this paper, we propose a statistical composition for the lifetime prediction based on the active and sleep probability of the participating sensor nodes in the network. This approach is able to estimate the collapse time of the entire network. It identifies two key attributes of the network that might affect the network lifetime. The key attributes are the node density and active-sleep transition characteristic of the nodes. The simulation results further establish the relevance of the analytical study and assert that the overall network lifetime is increased as the node density is increased in general. But, on the contrary, the comprehensive energy necessity of the network is also increased. A trade-off between these two factors is observed by changing the active-sleep transition characteristics of the nodes in the network.
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Dasgupta, S., Dutta, P. (2020). A Study on Collapse Time Analysis of Behaviorally Changing Nodes in Static Wireless Sensor Network. In: Mandal, J., Sinha, D. (eds) Intelligent Computing Paradigm: Recent Trends. Studies in Computational Intelligence, vol 784. Springer, Singapore. https://doi.org/10.1007/978-981-13-7334-3_2
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DOI: https://doi.org/10.1007/978-981-13-7334-3_2
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