New computations of the fractional worms transmission model in wireless sensor network in view of new integral transform with statistical analysis; an analysis of information and communication technologies

被引:3
|
作者
Rashid, Saima [1 ]
Shafique, Rafia [1 ]
Akram, Saima [2 ,3 ]
Elagan, Sayed K. [4 ]
机构
[1] Govt Coll Univ, Dept Math, Faisalabad 38000, Pakistan
[2] Govt Coll Women Univ Faisalabad, Dept Math, Faisalabad 38000, Pakistan
[3] Bahauddin Zakariya, Ctr Adv Studies Pure & Appl Math, Multan 60000, Pakistan
[4] Taif Univ, Coll Sci, Dept Math & Stat, POB 11099, Taif 21944, Saudi Arabia
关键词
Worm transmission model; Wireless sensor network; Technology adoption; Social media network; Homotopy perturbation method; ZZ-transform; Atangana-Baleanu fractional derivative; Stability; Existence and uniqueness; EPIDEMIC MODEL; EQUATIONS; DERIVATIVES;
D O I
10.1016/j.heliyon.2024.e35955
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Wireless sensor networks (WSNs) have attracted a lot of interest due to their enormous potential for both military and civilian uses. Worm attacks can quickly target WSNs because of the network's weak security. The worm can spread throughout the network by interacting with a single unsafe node. Moreover, the analysis of worm spread in WSNs can benefit from the use of mathematical epidemic models. We suggest a five-compartment model to characterize the mechanisms of worm proliferation with respect to time in WSN. Taking into account the ZZ transform convoluted with the Atangana-Baleanu-Caputo (ABC) fractional derivative operator, we employ it to analyze the characteristics and applications of the ZZ transformation using the Mittag-Leffler kernel. Moreover, we construct a new algorithm for the homotopy perturbation method (HPM) in conjunction with the ZZ transform technique to generate analytical solutions for the worm transmission model. Also, we address the qualitative aspects such as positivity, boundness, worm- free state, endemic state, basic reproduction number (R0) and worm-free equilibrium stability. Furthermore, we prove that the virus rate in sensor nodes is extinct if R-0 < 1 and the virus persists if R-0 > 0 . In addition, we develop analytical findings to evaluate the series of solutions. Furthermore, a detailed statistical analysis is conducted to verify the nonlinear dynamics of the system by verifying the 0 - 1 test to determine whether uncertainty exists using approximation entropy and the C-0 data. An extensive analysis of the vaccination class with respect to the transmitting class as well as the susceptible class is being used to investigate the effects of stepping up precautions on WP in WSN. Moreover, the modeling of the WSN revealed that reducing the fractional-order from 1 requires that the recommended approach be implemented at the highest rate so that there is no long-lasting immunization; instead, nodes remain briefly defensive before becoming vulnerable to future worm attacks.
引用
收藏
页数:30
相关论文
共 5 条
  • [1] Transmission model and statistical analysis for indoor wireless sensor network channels
    Yu, Y. (yuyan@dlut.edu.cn), 1600, Northeast University (29): : 1135 - 1138
  • [2] Proposal of a new Maximum Lifetime Communication Model of Wireless Sensor Network
    Lei, Jinhui
    Tian, Xiyan
    INTERNATIONAL JOURNAL OF ONLINE ENGINEERING, 2016, 12 (10) : 31 - 37
  • [3] Design and statistical analysis of a new chaotic block cipher for Wireless Sensor Networks
    Liu, Yanbing
    Tian, Simei
    Hu, Wenping
    Xing, Congcong
    COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION, 2012, 17 (08) : 3267 - 3278
  • [4] The Analysis of Fractional-Order Kersten-Krasil Shchik Coupled KdV System, via a New Integral Transform
    Shah, Nehad Ali
    Seikh, Asiful H.
    Chung, Jae Dong
    SYMMETRY-BASEL, 2021, 13 (09):
  • [5] New Configurations of the Fuzzy Fractional Differential Boussinesq Model with Application in Ocean Engineering and Their Analysis in Statistical Theory
    Chu, Yu-Ming
    Rashid, Saima
    Karim, Shazia
    Sultan, Anam
    CMES-COMPUTER MODELING IN ENGINEERING & SCIENCES, 2023, 137 (02): : 1573 - 1611