Optimal Cluster Head Selection in WSN with Convolutional Neural Network-Based Energy Level Prediction

Abstract

Currently, analysts in a variety of nations have developed various WSN clustering protocols. The major characteristic is the Low Energy Adaptive Clustering Hierarchy (LEACH), which attained the objective of energy balance by sporadically varying the Cluster Heads (CHs) in the region. Nevertheless, because it implements an arbitrary number system, the appropriateness of CH is complete with suspicions. In this paper, an optimal cluster head selection (CHS) model is developed regarding secure and energy-aware routing in the Wireless Sensor Network (WSN). Here, optimal CH is preferred based on distance, energy, security (risk probability), delay, trust evaluation (direct and indirect trust), and Received Signal Strength Indicator (RSSI). Here, the energy level is predicted using an improved Deep Convolutional Neural Network (DCNN). To choose the finest CH in WSN, Bald Eagle Assisted SSA (BEA-SSA) is employed in this work. Finally, the results authenticate the effectiveness of BEA-SSA linked to trust, RSSI, security, etc. The Packet Delivery Ratio (PDR) for 100 nodes is 0.98 at 500 rounds, which is high when compared to Grey Wolf Optimization (GWO), Multi-Objective Fractional Particle Lion Algorithm (MOFPL), Sparrow Search Algorithm (SSA), Bald Eagle Search optimization (BES), Rider Optimization (ROA), Hunger Games Search (HGS), Shark Smell Optimization (SSO), Rider-Cat Swarm Optimization (RCSO), and Firefly Cyclic Randomization (FCR) methods.

Distributed Consensus Kalman Filter Design with Dual Energy-Saving Strategy: Event-Triggered Schedule and Topological Transformation

“…In [ 29 ], the authors proposed a distributed topology control algorithm, which optimizes the topology based on the real-time residual energy of nodes. Similar works can be found in [ 30 , 31 , 32 , 33 , 34 , 35 ].…”

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

“…𝐶𝐶 𝑖 = (1/𝑐 𝑖 ) ∑ 𝑆𝑁 𝑖 𝑐 𝑖 𝑖=1 (10) In the above equation ( 10), the re-estimation of the new cluster centroid '𝐶𝐶 𝑖 ' is obtained. To ensure trust-based secure cluster formation an integer linear programming formulation considering the trusted neighbors with the cluster based on data traffic is designed.…”

“…Besides, the survey of security mechanisms required in the creation of clusters and mechanisms to mitigate in detail was investigated in [5]. In [10], the Bald Eagle mechanism utilizing energy and security factors was implemented to ensure the best PDR by trust factor. A hybrid trust-based mechanism employing ML methods was presented in [13].…”

Hybrid Optimization Algorithm of OAFS and ICS with CNN-based Energy Level Prediction for Wireless Sensor Networks

“…After the energy has been calculated, an enhanced version of DCNN may be used to estimate the energy level [23]. This di is used to make predictions about the SN energy.…”