Epidemic theory and data survivability in unattended wireless sensor networks: Models and gaps

Information survivability is the capability of a system to fulfill its mission, in a timely manner, and even in the presence of attacks, failures, or accidents. In this paper, we provide a preliminary assessment of epidemic-domain inspired approaches to model the information survivability in UWSNs. In particular, we show that epidemic models can be used to devise solutions enabling the information to survive, once the maximal compromising power of an attacker is estimated. However, we also point out that the mere application of these models is not always the right choice. Indeed, our results show that these deterministic models are not accurate enough, and “unlikely” events—usually met when striving to optimize resource usage—can cause the loss of the datum; furthermore, we highlight that when translating these models into real applications, geometric constraints (such as communication radius and deployment area) can hinder the applicability of epidemic models. We propose a simple but effective solution to these issues. Finally, extensive simulations support our results.