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An Analytical Model for Information Centric Internet of Things Networks in Opportunistic Scenarios

The availability of environmental monitoring data collected by Internet of Things networks can be essential for many critical processes, such as relief operations in disaster areas. The underlying communications infrastructure can be however severely compromised in these scenarios and therefore opportunistic approaches might be needed. Approaches based on information centric networks (ICN), where moving devices forward collected data, have been proposed for opportunistic scenarios but to date, the dynamics of the delivery process in ICNs remain poorly understood. In this paper, we build a family of Markovian models for the delivery process of ICNs in opportunistic scenarios, that allow us to derive the end-to-end delay distribution and the storage ratio in terms of the encounter rate of the moving devices. Furthermore, we investigate how prefetching mechanisms affect the delivery process compared to conventional ICNs. The proposed models are fully validated in a computer simulation environment and demonstrate that the utility of delivery with prefetching reaches its peak in a short time and then decreases at a high rate. Our Markovian models can provide both the insight and quantitative estimations that are needed to design practical ICNs in opportunistic scenarios.