@article{MAKHILLJEAS2017122315280,
    title = {FEELP: Fuzzy-Based Energy-Efficient LEACH Protocol in
Wireless Sensor Networks},
    journal = {Journal of Engineering and Applied Sciences},
    volume = {12},
    number = {23},
    pages = {7201-7207},
    year = {2017},
    issn = {1816-949x},
    doi = {jeasci.2017.7201.7207},
    url = {https://makhillpublications.co/view-article.php?issn=1816-949x&doi=jeasci.2017.7201.7207},
    author = {A. and},
    keywords = {Cluster formation,energy-efficiency,LEACH protocol,super cluster head,wireless sensor,SCH},
    abstract = {Wireless Sensor Networks (WSNs) brings a great solution for most of the areas where the
infrastructure is not accessible. This motivates the improvement on WSNs and increases the necessity of such
networks. The most annoying factor of WSN is that mostly the network is placed in some hostile area and it
cannot be able to replace the battery of the nodes. Such problems introduce the need of energy-efficient
protocol to extend the lifetime of the network. The group of nodes are formed as clusters and controlled by
Cluster Head (CH). The election of CH is a tedious process which gives a lifetime opportunity to the entire
network. The Low Energy Adaptive Cluster Hierarchy (LEACH) protocol follows the election using the
threshold function. In this model, the threshold function of LEACH is modified to elect a better and high
performing CH to extent the network lifetime using residual energy, distance to Base Station (BS) and threshold
energy of a node. The node which gets the higher value among the other member nodes is elected as CH. This
model also introduces a novel idea to elect Super CH (SCH) among the elected CH which will receive the
information from other CH’s and forwards it BS. The aggregation will also be done at SCH. The Fuzzy Logic (FL)
is been introduced in this approach to elect SCH. The proposed scheme is verified with the latest existing
models. The simulation results show that the proposed model performs better than the existing models in terms
of average energy, average distance to BS and other empirical metrics.}
    }