Title: Neural network-based virtual backbone tree construction and dynamic sink implementation to enhance the lifetime of the network and minimise the energy consumption

Authors: Stephen K. Vimal Kumar; V. Mathivanan

Addresses: Department of Computer Science and Engineering, AMET University, Chennai, Tamilnadu, India ' Department of Computer Science and Engineering, AMET University, Chennai, Tamilnadu, India

Abstract: With the effect of technological development, the primary objective of this research aims at retaining the energy level of the sensor node for a long period in the wireless sensor network. Ensuring negligible energy drop leads to long life for the network. Secure group key management technique is imposed to solve the security problem such as authentication, confidentiality and scalability. Cluster key and master key is exclusively used in the network to protect the sensed information while communication between nodes takes place. Static and movable mobile sinks are deployed to enhance the lifetimes of the sensors in the network. Initially, the static mobile sinks act as a trusted third party for computing and distributing keys between sensor nodes and the clusters. Further, movable sinks are used to receive sensed data from the sensor where it is being located which avoids unnecessary event of choosing new cluster head often. The energy is retained, since the presence of trusted third party sink performs all the computations of cluster head. Computation is reduced in cluster head thereby increases the life time of the particular cluster. Outcomes of experiments prove that the suggested technique produced better results compared to related study.

Keywords: wireless network; dynamic sink; static sink; security; neural network; virtual backbone tree; energy consumption; life time of a network; cluster key; master key; feed forward network; fault tolerant.

DOI: 10.1504/IJAIP.2019.101981

International Journal of Advanced Intelligence Paradigms, 2019 Vol.13 No.3/4, pp.304 - 323

Received: 07 Dec 2016
Accepted: 18 Feb 2017

Published online: 03 Sep 2019 *

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