COMBINED ANALYSE TRUST SECURE ROUTING STRATEGY AND BUILD A GENTIC FUZY BASED MODEL FOR WIRELESS SENSOR NETWORKS
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Abstract
In recent times, the development sensors wirelessly have been an essential requirement for cuttingedge
areas like environment surveillance and intelligent cities. En-route filtering systems are mainly
focused on energy efficiency by preventing fraudulent report injection attacks. However, the lifetime
of networks is typically neglected. They also have fixed path routing as well as fixed responses to
attacks. Additionally, the hot-spot issue is regarded as one of the biggest problems in the extension of
network life. In this paper, we propose an algorithmic basis for a fuzzy genetic optimized re-clustering
technique to overcome these restrictions and thus reduce the impact of the hot-spot issue. This fuzzy
algorithm is employed to analyze the network conditions. In re-clustering key issue is when to
conduct the subsequent clustering. To determine the exact time of the next clustering (i.e. the energy
draining from the nodes to zero) as well as the fuzzy member functions are optimized by using a the
genetic algorithm. Simulation tests verify the proposed algorithm. It has shown that the network's
lifetime can be extended by up to 3.64 times while maintaining the detection capability and energy
efficiency.
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