EiSIRS: a formal model to analyze the dynamics of worm propagation in wireless sensor networks

The SEIQR–V Model: On a More Accurate Analytical Characterization of Malicious Threat Defense

“…The fact that sensor nodes can become dead due to the depletion of their minimal battery power motivated Wang and Li [14] to propose the nonlinear iSIR model which describes malware patterns in large sensor networks. Using Vinsim 5.0 -a system dynamics software, they simulated three hypothetical cases of the random features of state transition in WSN.…”

“…Due to the absence of a popular policy for elongating the life time of sensors in [14], Wang, Li and Li [15] proposed the EiSIRS model which considers the sleep and work interleaving schedule for nodes. This model unlike the model in [14] does not assume that the sensors work all the time i.e.…”

“…This model unlike the model in [14] does not assume that the sensors work all the time i.e. the susceptible, the infectious and the recovered nodes can be in either sleeping or working mode.…”

“…While Tang and Mark [13], Wang and Yang [18] used a certain expression for uniform random distribution, Feng et al [22] employed the expression used by Wang and Li [14] to evaluate the impact of communication radius, energy consumption and node distribution density in WSN. In their work the jacobian method was used to investigate the local stability while the lyapunov theorem was used to study the global stability.…”

“…In this study, the SEIQR-V is modified to include the analysis for the impact of transmission range and density. The topological expressions described in Tang and Mark [13], Wang and Yang [18] and Feng et al [22] and Wang and Li [14] will prove useful.…”