TY  - JOUR
T1  - An Intelligent Optimization Algorithm for Optimal Route Selection for
Wireless Sensor Networks
AU - Manikandan, V. AU - Sivaram, M. AU - Salih Mohammed, Amin AU - Porkodi, V. 
JO  - Journal of Engineering and Applied Sciences
VL  - 14
IS  - 17
SP  - 6510
EP  - 6518
PY  - 2019
DA  - 2001/08/19
SN  - 1816-949x
DO  - jeasci.2019.6510.6518
UR  - https://makhillpublications.co/view-article.php?doi=jeasci.2019.6510.6518
KW  - WSN
KW  -cuckoo search
KW  -Markov Model
KW  -energy utilization
KW  -routing strategy
KW  -EAR protocol
AB  - In Wireless Sensor Networks (WSN), sensor nodes makes use of battery energy, routing and energy
consumption along with certain limitations of sensor nodes are considered as a preliminary challenges and
problems associated with WSN. In recent times, in WSNs, identification of successive nodes based on the
localization and the energy minimization can be achieved by partitioning the nodes into clusters at the central
region. In this manner, this research attempts to maintain energy consumption using optimal cuckoo search
model in the network nodes. While comparing this with conventional models, the proposed model for energy
estimation attains finest efficiency in relation to improvement in network lifetime. In this investigation, cuckoo
optimization algorithm with Markov Chain model for successive identification of transition state is performed
in WSN environment for identifying the optimal nodes for multi-hop routing and estimating energy. The
anticipated strategy is measured in three specific criteria, nodes successive life time, energy utilization, end to
end delay with targeted CMMRR algorithm, the residual energy, distance amongst the nodes and cluster head
distance is also observed. The outcomes of simulating the anticipated CMMRR method are done in MATLAB
environment. The outcomes of the proposed method is compared with the existing techniques like EAR Model,
the proposed method shows better trade off 10.4-29% over prevailing EAR protocol in terms of packet delivery
ratio, nodes life time and so on.
ER  -