dc.contributor.author |
Dadhirao, Chandrika |
|
dc.contributor.author |
Sangam, Ravi Sankar |
|
dc.date.accessioned |
2022-12-06T19:57:43Z |
|
dc.date.available |
2022-12-06T19:57:43Z |
|
dc.date.issued |
2022-12-06 |
|
dc.identifier.issn |
2210-142X |
|
dc.identifier.uri |
https://journal.uob.edu.bh:443/handle/123456789/4698 |
|
dc.description.abstract |
The Wireless Sensor Networks is the collection of sensor nodes that can sense the environment and send it to the sink or access
point for further processing based on the requirement. It works on the principle of ”less effort and more comfort.” These sensors collect
the sensed data and transfer it to the access point. The Network framework is critical in selecting the optimum distance and degree of
data-access point connectivity for effective communication between source, intermediate destinations, and the final destination. For this,
Energy-efficient clustering is the ultimate mechanism for long-term energy efficiency in most Networks. To achieve long-term energy
efficiency, we choose to enhance the LEACH protocol as it is a well-known protocol for energy efficiency and prolongs the network
lifetime. Still, the cons of the LEACH protocol are it uses a random approach for cluster formation. It does not consider the node’s
residual energy for choosing the head node from each cluster. We enhanced the LEACH protocol by using an Adaptive network-based
fuzzy inference system by overcoming the mentioned cons. We conducted a simulation to test the efficiency of our proposed routing
protocol. It is better in terms of throughput, lifetime, energy dissipation, and the first node dies, quarter node dies, percent of
node die, and several nodes alive after completion of rounds. Also, we compared our approach with two of the existing state of art
approaches like LEACH using the Conventional approach, LEACH using the Fuzzy approach, and Multi-Criteria Cluster Head Delegation. |
en_US |
dc.language.iso |
en |
en_US |
dc.publisher |
University of Bahrain |
en_US |
dc.subject |
Wireless Sensor Networks, ANFIS, Routing Protocol, Clustering, Head Node , Network Lifetime , Energy Efficiency |
en_US |
dc.title |
Elongate the Network Lifetime using Adaptive Network-Based Fuzzy Inference System in Wireless Sensor Networks |
en_US |
dc.type |
Article |
en_US |
dc.identifier.doi |
https://dx.doi.org/10.12785/ijcds/1201107 |
|
dc.volume |
12 |
en_US |
dc.issue |
1 |
en_US |
dc.pagestart |
1329 |
en_US |
dc.pageend |
1342 |
en_US |
dc.contributor.authoraffiliation |
Research Scholar,School of Computer Science and Engineering, VIT-AP University, near vijayawada,A.P, India |
en_US |
dc.contributor.authoraffiliation |
Associate Professor,School of Computer Science and Engineering, VIT-AP University, near vijayawada, A.P, India |
en_US |
dc.source.title |
International Journal of Computing and Digital Systems |
en_US |
dc.abbreviatedsourcetitle |
IJCDS |
en_US |