Title :
Congestion detection in Wireless sensor network using neural network
Author :
Singhal, Prakul ; Yadav, Anamika
Author_Institution :
Dept. of Electr. Eng., Nat. Inst. of Technol., Raipur, Raipur, India
Abstract :
In Wireless sensor network (WSN), sink nodes are bottleneck of network due to congestion. Congestion deteriorates the overall performance of the system. So congestion detection in a WSN is very vital issue in the present scenario. In this paper, artificial neural network based congestion detection algorithm is developed. The neural network based congestion detection system uses number of participants, buffer occupancy, and traffic rate as input parameters and gives the congestion level as output. A number of NS-2 and MATLAB simulation results show that the proposed scheme accurately detects the congestion level and represents the state of congestion in the WSN.
Keywords :
Internet; neural nets; telecommunication congestion control; wireless sensor networks; Matlab simulation; NS-2; WSN; artificial neural network based congestion detection algorithm; buffer occupancy; congestion level; input parameters; participant number; sink nodes; traffic rate; wireless sensor network; Artificial neural networks; Biological neural networks; MATLAB; Protocols; Training; Wireless sensor networks; Buffer occupancy; Congestion detection; Neural network; Traffic rate; Wireless sensor network;
Conference_Titel :
Convergence of Technology (I2CT), 2014 International Conference for
Print_ISBN :
978-1-4799-3758-5
DOI :
10.1109/I2CT.2014.7092259