Dual-Tier Cluster-Based Routing in Mobile Wireless Sensor Network for IoT Application

Abstract

Mobile wireless sensor network (MWSN) technology is a fundamental element of the Internet of Things (IoT) in which hundreds to thousands of sensor nodes (SNs) are connected via wireless channels capable of providing a digital interface to real-life objects. Energy consumption, connectivity, scalability, and security are the main challenges in MWSN, and mobility increases the effort required to find an efficient routing protocol to improve the MWSN performance. In this paper, we propose a novel routing protocol based on the dual-tier clustering concept and virtual network zones to improve MWSN performance. The proposed protocol named "Dual Tier Cluster-Based Routing" (DTC-BR) divides the network area into virtual zones which a cluster-head mechanism selects the most appropriate SN to act as Cluster Head (CH). Furthermore, virtual zones are designed to cover the entire network area based on a dual-tier routing mechanism: the main connectivity zone (MCZ) and candidate cluster zone (CCZ). The DTC-BR protocol was deployed and assessed using MATLAB, assuming three levels: energy consumption, network lifetime, and scalability. The comparative results demonstrate the efficiency of DTC-BR, where the network lifetime increased by 6%, 21%, 25%, and 37% compared to state-of-the-art dynamic directional routing (DDR), mobility-aware centralised clustering algorithm (MCCA), low-energy adaptive clustering hierarchy-mobile energy efficient and connected (LEACH-MEEC), and low-energy adaptive clustering hierarchy mobile (LEACH-M) protocols, respectively. In addition, the simulation results show that DTC-BR is more efficient for large network sizes and a high number of SNs.INDEX TERMS Mobile Wireless Sensor Network (MWSN), cluster-based routing, Cluster Head (CH), virtual zone, energy-efficient

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

“…Figure 10 shows 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.…”

“…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.…”

“…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.…”

Artificial Intelligence-based Cayley Menger Securex-means Clustering and Hyper Gradient Reliable Data Transmission in Wsn

“…A dual-tier clustering-based method for WSN to focus on several performance parameter aspects like network lifetime, scalability and energy consumption was designed in [11]. In [12],…”

“…To be more specific, the problem was formulated as a Gaussian Mixture Model (GMM) using equivalence constraint and Expectation Maximization (EM) algorithm for clustering. A dualtier clustering-based method for WSN to focus on several performance parameters aspects like network lifetime, scalability, and energy consumption was designed in [11]. In [12], the distributed learning mechanism was implemented based on the game theory principles.…”