Open AccessHEEL: A new clustering method to improve wireless sensor network lifetime
Author(s) -
Seyyedabbasi Amir,
Dogan Gulustan,
Kiani Farzad
Publication year - 2020
Publication title -
iet wireless sensor systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.433
H-Index - 27
eISSN - 2043-6394
pISSN - 2043-6386
DOI - 10.1049/iet-wss.2019.0153
Subject(s) - wireless sensor network , cluster analysis , computer science , node (physics) , computer network , key distribution in wireless sensor networks , sensor node , distributed computing , real time computing , wireless network , engineering , wireless , artificial intelligence , telecommunications , structural engineering
In wireless sensor networks, some resources such as memory and energy are limited. In recent years, there has been an increasing interest in improving network lifetime. Node energy plays an important role in the network lifetime. Along with this remarkable growth in wireless sensor networks, however, there is an increasing concern over network lifetime. The principal purpose of this study is to develop an understanding of the effects of other parameters on selecting a cluster head. The methodological approach taken in this study is a mixed methodology typically based on the node's energy. The authors have operated four parameters to select the cluster head: Node energy, the energy of the node's neighbours, number of hops and number of links to neighbours. Each of these parameters has an impact in selecting the cluster head. They accurately observed hop size, energy of each sensor node, average energy of sensor neighbours, links to sensor nodes (HEEL) has better improvements in comparison of Node ranked Low Energy Adaptive Clustering Hierarchy (Nr‐LEACH), Modified Low Energy Adaptive Clustering Hierarchy (ModLEACH), Low Energy Adaptive Clustering Hierarchy‐B (LEACH‐B), Low Energy Adaptive Clustering Hierarchy (LEACH), Power‐Efficient Gathering in Sensor Information System (PEGASIS), energy‐aware clustering scheme with transmission power control for sensor networks (EACLE) and hybrid energy efficient distributed clustering (HEED) algorithms in possible case of network lifetime and throughput.