K-Means Based Bee Colony Optimization for Clustering in Heterogeneous Sensor Network
Prince Modey, Gaddafi Abdul-Salaam, Emmanuel Freeman, Patrick Acheampong, William Leslie Brown-Acquaye, Israel Edem Agbehadji, Richard C Millham, Sebastià Galmés, Baris Atakan · 2024
Read K-Means Based Bee Colony Optimization for Clustering in Heterogeneous Sensor Network by Prince Modey, Gaddafi Abdul-Salaam, Emmanuel Freeman, Patrick Acheampong, William Leslie Brown-Acquaye, Israel Edem Agbehadji, Richard C Millham, Sebastià Galmés, Baris Atakan (2024) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/pmc-11645032.txt.
Description
Prince Modey and co-authors propose a better way to group sensors in a wireless network, in work published in 2024. In such networks, many small sensors send data through group heads, and smart grouping saves battery power. The classic bee colony method used for this task often wastes energy. The team mixed that method with a well-known grouping method called K-means.
The new method, named K-BCO, was tested against three rival methods for grouping sensors. It sent data more reliably, with a delivery rate of 95 percent, above all three rivals. It also used less energy on average and made fewer errors when passing data to group heads. The authors say the mix gives steadier results and longer network life, and they commend it to people who build and run sensor networks.
Catalog record
| CREATOR | Prince Modey, Gaddafi Abdul-Salaam, Emmanuel Freeman, Patrick Acheampong, William Leslie Brown-Acquaye, Israel Edem Agbehadji, Richard C Millham, Sebastià Galmés, Baris Atakan |
|---|---|
| YEAR | 2024 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 59 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |