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<a target="_blank" rel="noopener" href="https://fatcat.wiki/container/qty27capxvbkfojct55lrrgazm" style="color: black;">International Journal on Soft Computing Artificial Intelligence and Applications</a>
Wireless Sensor Networks (WSNs) are defined as dynamic, self-deployed, highly constrained structured network. It's high computational environment with limited and controlled transmission range, processing, as well as limited energy sources. The sever power constraints strongly affect the existence of active nodes and hence the network lifetime. In order to prolong the network life time we have to overcome the scarcity in energy resources and preserve the processing of the sensor nodes as long<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.5121/ijscai.2013.2403">doi:10.5121/ijscai.2013.2403</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/olxmn25qtffxjjlwtvpp7arepe">fatcat:olxmn25qtffxjjlwtvpp7arepe</a> </span>
more »... possible. Power management approaches efficiently reduce the sensor nodes energy consumption individually in each sensor node and the adaptive efficient routing technique has greatly appeals a great attention in research. The potential paradigms of soft-computing (SC) highly addressed their adaptability and compatibility to overwhelm the complex challenges in WSNs. This paper is introducing and surveying some of the Soft Computing proposed routing models for WSNs that optimally prolongs its life time.
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