epidemic data survivability in unattended wireless sensor networks
A recent research thread focused on Unattended Wireless Sensor Networks (UWSNs), that are characterized by the intermittent presence of the sink. An adversary can take advantage of this behavior trying to erase a piece of information sensed by the network before the sink collects it. Therefore, without a mechanism in place to assure data availability, the sink will not ever know that a datum has been compromised. In this paper, we adopt data replication to assure data survivability in UWSNs. In particular, we revisit an epidemic model and show that, even if the data replication process can be modelled as the spreading of a disease in a finite population, new problems that have not been discovered before arise: optimal parameters choice for the model do not assure the intended data survivability. The problem is complicated by the fact that it is driven by two conflicting parameters: On the one hand the flooding of the datum has to be avoided---due to the sensor resource constraints---, while on the other hand data survivability depends on the data replication rate. Using advanced probabilistic tools we achieve a theoretically sound result that assures at the same time: Data survivability, an optimal usage of sensors resources, and a fast and predictable collecting time. These results have been achieved in both the full visibility and the geometrical model. Finally, extensive simulation results support our findings.
data survivability unattended wireless sensor network epidemic models