Identification of Disconnected Components in WSN for Secure Big Data Gathering
Tanuj Wala, Narottam Chand, Ajay K. Sharma · 2018 Second International Conference on Electronics, Communication and Aerospace Technology (ICECA) · 2018
Recent technological advancements have enabled a significant evolution and grouping of wireless sensor networks (WSNs). These webs of networks are key player in Internet of Things (IoT) that generate huge amount of exponentially increasing data popularly called as big data. Gathering secure big data with energy efficiency for widely and densely distributed wireless sensor networks is mind triggering task due to restrained wireless communication range and low power nature of sensor nodes. Connectivity of sensor nodes is an important issue in wide and distributed wireless sensor network. Also the mechanism of multihop routing does not support such networks due to the problem of long transmission delays and existence of disconnectivity in networks. Due to this, there arises the problem of data loss and huge consumption of power. This paper considers the problem of identification of disconnected components in wireless sensor network. To achieve the objective Spectral Graph Partitioning (SGP) technique is used. SGP technique calculates the eigenvalues and eigenvectors for network as per the Laplacian matrix of the network graph. To detect the disconnected components in the network SGP observes the lowest eigenvalues. The given example illustrates the concept and findings of the technique being implemented to achieve the solution.