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- W3022811042 abstract "This paper proposed a hybrid bacterial foraging optimisation (BFO) and fruitfly optimisation algorithm (FOA) for energy efficient cluster head (CH) selection in wireless sensor network. The bacterial foraging optimisation algorithm is inspired by the group foraging behaviour of bacteria such as E. coli and M. xanthus realising chemistry in the environment and moving away from specific signals. The FOA is simple framework and easy to implement for solving an optimisation problem with different characteristics. It is robust and fast algorithm and used to solve discrete optimisation problems. The performance metrics of the proposed method is evaluated for end to end delay, packet delivery, drop ratio, energy consumption, network lifetime and throughput. The simulation results show that the proposed method achieves better energy efficiency and network lifetime of 35%, 58%, and 67% compared to existing methods like ant colony optimisation, particle swarm optimisation and genetic algorithm." @default.
- W3022811042 created "2020-05-13" @default.
- W3022811042 creator A5047886019 @default.
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- W3022811042 date "2020-01-01" @default.
- W3022811042 modified "2023-09-25" @default.
- W3022811042 title "A hybrid BFO-FOA-based energy efficient cluster head selection in energy harvesting wireless sensor network" @default.
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- W3022811042 doi "https://doi.org/10.1504/ijcnds.2020.10029290" @default.
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