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- W2963721014 abstract "In this generation of advance technologies, where communication between physical devices is vital, Internet of Things(IoT) play an important part in connecting the cyber and physical world. IoT is used in various applications such as agriculture, smart home and smart cities, through the deployment of Wireless Sensor Networks(WSNs). Although, in hostile environments, where human intervention is impossible, the life cycle of a deployed WSN becomes critical. Conserving the energy consumed by a wireless sensor network, is imperative, in prolonging the life cycle of the network. This paper addresses the challenging issue of minimizing the energy consumption of WSNs on a large scale. The contributions made by this paper are using the optimization model proposed in [25] to compare Genetic Algorithm(GA) and the Mixed Integer Linear Programming(MILP) algorithm, to solve the minimum energy consumption problem for an IoT. The MILP and GA approach in solving the minimum energy consumption problem, is flexible and efficient, and helps us to achieve our goal, i.e. minimum energy consumption and maximum network lifetime of a deployed WSN." @default.
- W2963721014 created "2019-07-30" @default.
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- W2963721014 date "2019-04-01" @default.
- W2963721014 modified "2023-09-25" @default.
- W2963721014 title "Evolution-Based Deployment Scheme for Green Internet of Things" @default.
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- W2963721014 doi "https://doi.org/10.1109/wf-iot.2019.8767303" @default.
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