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- W4282915728 abstract "A wireless sensor network (WSN) is an assortment of sensor nodes proficient in environmental information sensing, refining it and transmitting it to the base station in a sovereign manner. The minute sensors communicate themselves to sense and monitor the environment. The main challenges are limited power, short communication range, low-bandwidth and limited processing. The power source of these sensor nodes is the main hurdle in the design of energy-efficient network. The main objective of the proposed clustering and data transmission algorithm is to augment network performance by using the swarm intelligence approach. This technique is based on k-mean-based clustering and ant colony optimisation-based data forwarding. The proposed algorithm KACO is divided into two parts: (1) Clustering of sensor nodes using k-mean technique and (2) using the shortest path for data transmission based on ant colony optimisation (ACO) technique. The performance is evaluated in terms of throughput, packet delivery ratio, energy dissipation and residual energy analysis." @default.
- W4282915728 created "2022-06-16" @default.
- W4282915728 creator A5061962496 @default.
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- W4282915728 date "2022-06-14" @default.
- W4282915728 modified "2023-09-29" @default.
- W4282915728 title "KACO: k-mean clustering and ACO-based data transmission in wireless sensor networks" @default.
- W4282915728 doi "https://doi.org/10.1201/9781003340867-18" @default.
- W4282915728 hasPublicationYear "2022" @default.
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