Coverage hole aware optimal cluster based routing for wireless sensor network assisted IoT using hybrid deep recurrent neural network

Abstract

Nowadays, the wireless sensor network (WSN) with IoT is intended to monitor real-world physical or environmental phenomena in a number of applications, including foreign areas such as health and habitat monitoring. The WSN-IoT network generates huge volume of data, which has to be processed and accessed by the remote users. Due to this large volume of data generation and resource constraint ability make achieving optimal cluster based routing in WSN-IoT. The location of the sensor nodes significantly affects the accuracy of the information collected, which determines the quality of service provided by the application system. WSN can have multiple conflicts, which can create different coverage holes. These holes will break the existing overlap or connection and affect the required operation of the networks. Therefore, it is essential to find and repair the coverage holes to ensure the full functioning of the WSN as a motivation of this study. In this paper, we suggest a novel Coverage Hole aware Optimal Cluster based Routing (CHOCR) scheme for WSN-IoT. First, we propose Modified Lichtenberg optimization (MLO) algorithm for balanced clustering which improve the performance of coverage hole. Second, we develop a linear equilibrium optimization based decision making (LEO-DM) technique to subtract trust value of each IoT node using multiple restraints in cluster and consider the highest trusted node is act as cluster head (CH). After that, a hybrid deep recurrent neural network (HD-RNN) is developed for intermediate node selection to frame the routing between two nodes.Finally, we simulate our proposed CHOCR scheme on the NS3.26 simulator. According to energy consumption, network longevity, number of nodes that are still alive and packet delivery ratio, packet loss ratio and throughput, end-to-end latency and delay of our proposed CHOCR routing system, we compare it to other current routing schemes.

Energy-Efficient Secure Routing for a Sustainable Heterogeneous IoT Network Management

“…The average energy effect is measured to show the superiority of the proposed model for energy consumption. For the proposed CHOCR [35], IMD-EACBR [36], IDR-DRL-DC [37] and DTC-BR [38] obtained average energy effect of 90, 92, 95, 95 and 90 (%), respectively. Thus, the energy consumption of the model has been minimized effectively.…”

“…The proposed model obtained 98.05, 98.01, 98.06, 98, 98.01, 98.05, 98.05, 98.05 and 98.01 (%), respectively, where exiting models attained a very low percentage.Figure10shows the computational complexity of the model in terms of time O N 2 . From this, it has been proven that the proposed model attained a minimum time complexity of 18.9%, while others such as CHOCR[35], IMD-EACBR[36], IDR-DRL-DC[37] and DTC-BR[38] attained 22, 24, 22 and 23 (%), respectively. Thus, the proposed model was proven to be effective.…”

“…From the figure, it is clear that the proposed model attained better packet loss, which was due to security measures taken against cyber security attacks. Those proposed, CHOCR [35], IMD-EACBR [36], IDR-DRL-DC [37] and DTC-BR [38], obtained a loss ratio of 12, 15, 17, 21 and 22%, respectively. Thus, overall, the proposed model excels more than previous ones.…”

Distributed WSN Vulnerability Remediation System Based on Mobile-N Policy

“…( 4), while the polygonal intersection needs to determine the coordinates of the intersection point of the different nodes and to determine the positional relationship with another node. Therefore, the area of overlapping part of polygonal intersection can be calculated by formula (5).…”

“…However, these methods often cannot completely prevent attacks from occurring, and once the network is attacked, the damaged network nodes or paths need to be repaired in a timely manner to ensure the normal operation of the network [4][5][6]. In recent years, mobile node-based repair strategies have attracted much attention.…”