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Abstract-We study the potential threat for virus spread in wireless sensor networks (WSNs). Using epidemic theory, we proposed a new model, called Susceptible-Infective-Recovered with Maintenance (SIR-M), to characterize the dynamics of the virus spread process from a single node to the entire network. By introducing a maintenance mechanism in the sleep mode of WSNs, the SIR-M model can improve the network's anti-virus capability and enable the network to adapt flexibly to different types of viruses, without incurring additional computational or signaling overhead. The proposed model can capture both the spatial and temporal dynamics of the virus spread process. We derive explicit analytical solutions for the model and discuss some practical applications of interest. Extensive numerical results are presented to validate our analysis. The proposed model is applicable to the design and analysis of information propagation mechanisms in communication networks.

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Abstract-We analyze the performance of a wireless system that allows opportunistic spectrum sharing. The system consists of a set of primary users sharing a set of channels over a coverage area. The resources allocated to the primary users are shared opportunistically with a set of secondary users. The secondary users are capable of detecting channels that are unused by the primary users and then making use of the idle channels. If no channel is available for a secondary call, the call waits in a buffer until either a channel becomes available or a maximum waiting time is reached. We compute the blocking probabilities, mean reconnection probability, channel utilization, and total carried traffic in the system. Our results suggest that opportunistic spectrum sharing can significantly improve the efficiency of a wireless system, without negatively impacting the performance seen by the primary users.

We study the dynamics of virus spread in wireless sensor networks (WSNs). We first analyze the susceptible-infective (SI) epidemic model for WSNs. In the SI model, once a sensor node is attacked by a virus, the infective node then, using normal communications, spreads the virus to its neighboring nodes, which further spread the virus to their neighbors, the process continues until the whole network fails. To combat this drawback, we propose a modified SI model by leveraging the sleep mode of WSNs to perform system maintenance. The modified SI model can improve the network anti-virus capability and flexibly adapt to different types of virus, without causing any additional hardware effort and signaling overhead. We derive the explicit analytical solutions for the modified SI model, which can capture both the spatial and temporal dynamics of the virus spread process. Extensive numerical results are presented to validate our analysis. The proposed model and analysis method are expected to be used for analysis and design of information (including virus) propagation mechanisms in distributed wireless or computer networks.