Indian Journal of Science and Technology
DOI: 10.17485/ijst/2015/v8i12/63283
Year: 2015, Volume: 8, Issue: 12, Pages: 1-5
Original Article
R. Abinaya* and S. Kamakshi
School of Computing, SASTRA University, Thanjavur, Tamilnadu, India; [email protected], [email protected]
The service provided by the Wireless Sensor Networks (WSN) should provide better quality as Quality of the network plays an important role in the improving the performance of the system. The dynamic topology and resource constraints of WSN are highly challenging in achieving QoS. Thus in this paper Quality of Service (QoS) is improved for some of the QoS parameters like packet loss and congestion. Categorization of nodes as qualified and unqualified is done using the parameters. The quality node then dynamically forms a network. A novel method to improve the QoS based on Artificial Neural Network (ANN) is used to train the unqualified nodes to make them as quality nodes. The structure of Artificial Neural Networks provides less complexity compared to other Computational Intelligence (CI) tools as wireless sensor networks are prone to many constraints like memory and energy it reduces the computation cost and time. Our Simulation results shows that the proposed system has better performance in improving the QoS by increasing the network lifetime and reducing the packet loss ratio.
Keywords: Artificial Neural Networks, Congestion Rate, Qualified Nodes, Quality of Service, Packet Loss Ratio, Unqualified Nodes, Wireless Sensor Networks
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