Related Experiment Video
Updated: Jan 10, 2026

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
Published on: September 8, 2023
Controlling worm propagation in wireless sensor networks: Through fractal-fractional mathematical perspectives
Mian Imad Shah1, Eltigani Ismail Hassan2, Amjad Ali1
1Department of Mathematics and Statistics, University of Swat, Khyber Pakhtunkhwa, Pakistan.
Abstract:
Wireless Sensor Networks (WSNs) are particularly vulnerable to malware attacks due to their limited processing power, memory, and energy, which makes defending against such threats especially challenging. To mitigate these serious security issues caused by malware infection, various preventive measures can be implemented, such as honeypots, robust security protocols, hardware-based protections, regular updates, firewalls, and intrusion detection systems (IDS). Considering these security concerns, we adopt an advanced version of the existing susceptible-infectious-protected-recovered SIPR model that incorporates a fractional-fractal derivative (FFD) defined in the Atangana-Baleanu-Caputo (ABC) sense, which offers a more realistic representation than the classical model. Furthermore, this research work introduced a new isolated nodes compartment [Formula: see text], along with parameters [Formula: see text] and [Formula: see text], defining the recovery and isolation rates of [Formula: see text], respectively, in the existing SIPR model. Moreover, this study focuses on the existence and uniqueness of solutions, stability analysis, control theory and numerical approximation for the proposed generalized susceptible-infectious isolated-protected-recovered [Formula: see text] model. Additionally, nonlinear and fixed-point theory are used to obtain the results of existence and stability analysis. On the same line, Newton polynomial-based numerical scheme was established for the proposed modified model. The dynamics of desired results are visualized using MATLAB.
Related Concept Videos
Propagation of Uncertainty from Random Error
Gene Regulation in Microbial Communities: Quorum Sensing
SFG Algebra
Each node in an SFG corresponds to a variable, and the interactions between nodes are represented by branches with associated gains. When multiple branches lead into a node, the value at that node is the sum of the...

