Open AccessAn Improved Clustering Using by Likely Attributable Function and Informed Selection in WSN for Science of Management and Engineering
Author(s) -
Tarlan Motamedi Nia,
Rohollah Omidvar,
Elham Azarm
Publication year - 2021
Publication title -
journal of modern mechanical engineering and technology
Language(s) - English
Resource type - Journals
ISSN - 2409-9848
DOI - 10.31875/2409-9848.2021.08.10
Subject(s) - wireless sensor network , computer science , cluster analysis , computer network , energy consumption , key distribution in wireless sensor networks , protocol (science) , wireless , wireless network , data transmission , selection (genetic algorithm) , distributed computing , engineering , telecommunications , machine learning , medicine , alternative medicine , pathology , electrical engineering
Wireless sensors networks (WSNs) are traditionally composed of large number of tiny homogenous sensors nodes connected through a wireless network that gather data to be treated locally or relayed to the sink node through multi-hop wireless transmission. The low-energy adaptive clustering hierarchy (LEACH) protocol is one of the Famous protocols used in the wireless sensor networks (WSNs). The LEACH protocol in wireless sensor network suffers from many Bugs and many researchers proposed different methods to mitigate them. In this paper, we propose two ideas in a format for improving leach protocol. For Cluster head selection we used a Likely Attributable Function that in this function used from a factor. This factor that we called the informed selection factor helps to farther nodes not selection for cluster head. This significantly decreases the energy consumption and increases the lifetime of associated nodes. Simulation is conducted in using MATLAB results are analyzed for energy consumption.