TY - JOUR
T1 - System design of meb in M-IWD model with heuristic function on WSN
AU - Mohamed, Mohamed Yasin Noor
AU - Saleem Basha, M. S.
AU - Sujatha, Pothula
N1 - Publisher Copyright:
© 2021 Bentham Science Publishers.
PY - 2021
Y1 - 2021
N2 - Background: The Modified Intelligent Water Drop algorithm incorporated with the proposed heuristic function to enhance the characteristics of randomness, individual diversity to minimize the total energy required to broadcast the data from each sensor node towards the sink node in a network. Objective: The Modified Intelligent Water Drop Algorithm has been designed to achieve the divergence to find out an optimal Minimum Energy Broadcasting tree in WSN. Method: The proposed variant has been evaluated and compared concerning contemporary Evolutionary techniques using appropriate performance criteria. Result: To achieve optimum result, the proposed Modified Intelligent Water Drop algorithm compared with existing algorithm along with 20 nodes dataset with 30 instances, 50 nodes dataset with 30 instances and 100 nodes dataset with 30 instances. Conclusion: In this perspective, a suitable experimental setup has been designed and experiments are performed on different classes of Minimum Energy Broadcasting instances obtained from stand-ard Minimum Energy Broadcasting library [Comopt 2012] to validate the proposed Modified Intelligent Water Drop Algorithm. The simulation results of MEB for MIWD-HUD with convergence and divergence is given.
AB - Background: The Modified Intelligent Water Drop algorithm incorporated with the proposed heuristic function to enhance the characteristics of randomness, individual diversity to minimize the total energy required to broadcast the data from each sensor node towards the sink node in a network. Objective: The Modified Intelligent Water Drop Algorithm has been designed to achieve the divergence to find out an optimal Minimum Energy Broadcasting tree in WSN. Method: The proposed variant has been evaluated and compared concerning contemporary Evolutionary techniques using appropriate performance criteria. Result: To achieve optimum result, the proposed Modified Intelligent Water Drop algorithm compared with existing algorithm along with 20 nodes dataset with 30 instances, 50 nodes dataset with 30 instances and 100 nodes dataset with 30 instances. Conclusion: In this perspective, a suitable experimental setup has been designed and experiments are performed on different classes of Minimum Energy Broadcasting instances obtained from stand-ard Minimum Energy Broadcasting library [Comopt 2012] to validate the proposed Modified Intelligent Water Drop Algorithm. The simulation results of MEB for MIWD-HUD with convergence and divergence is given.
KW - Heuristic function
KW - Intelligent water drops algorithm
KW - M-IWD model
KW - Minimum energy broadcast
KW - System design
KW - Wireless sensor network
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U2 - 10.2174/1872212114999200521100146
DO - 10.2174/1872212114999200521100146
M3 - Article
AN - SCOPUS:85103104536
SN - 1872-2121
VL - 15
SP - 169
EP - 186
JO - Recent Patents on Engineering
JF - Recent Patents on Engineering
IS - 2
ER -