(c) 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works. Link to publisher version with DOI: https://ieeexplore.ieee.org/document/8396837/keywords#keywords. This work was supported the Spanish Government under contract TIN2016-77836-C2-2-R, and by the Generalitat de Catalunya as Consolidated Research Group 2017-SGR-990.

IoT systems monitoring or controlling the behavior of smart environments frequently require to count on real-time message delivery, in order to support decision making and eventually coordinate the individual behavior of their system components. Several initiatives propose the use of opportunistic networks to address this requirement, but none of them support message delivery considering time constraints. Therefore, the support that they provide is partially suitable for conducting real-time monitoring and control of smart environments. In order to address that challenge, this paper proposes a message propagation model for opportunistic networks that considers the participation of heterogeneous devices, and guarantees the real-time behavior of the network by bounding the maximum delay for messages transmission. The message propagation is modeled using an analytical approach that reduces the effort of prototyping and analyzing the properties of these networks. Two running examples, based on disaster relief efforts, are used to illustrate the feasibility of implementing the proposed message dissemination model on opportunistic networks and, thus, to allow real-time communication in the field. These results showed that is feasible not only the implementation of these networks but also their representation using an analytical approach. The networks for both example scenarios were then simulated to confirm the results obtained using the analytical approach. Given the positive results, the proposed model and its representation open several opportunities to model smart environments and design IoT systems that require real-time communication in opportunistic networks.

Peer Reviewed