Maximizing the Lifetime of Unreliable Sensor Networks with Delay Constraint via Genetic Algorithm

Energy saving is a key issue for prolonging the runtime of Wireless Sensor Network (WSN). In real-time applications of WSN, it is required to deliver data to the sink within a delay constraint. It is significant to design a scheme that maximizes the lifetime of WSN and satisfies delay constraint. To meet this requirement, in this paper, we present the Maximizing Lifetime and Delay Aware Scheme (MLDAS) that uses genetic algorithm, in which stochastic ranking (SR) method is applied, to find an Energy and Delay Aware Tree (EDAT) used to gather data in the WSN. Simulation results show that the MLDAS outperforms some existing schemes in terms of network lifetime and data accuracy.

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