Providing real-time message delivery on opportunistic networks
Author
dc.contributor.author
Santos, Rodrigo
Author
dc.contributor.author
Orozco, Javier
Author
dc.contributor.author
Ochoa Delorenzi, Sergio
Author
dc.contributor.author
Meseguer, Roc
Author
dc.contributor.author
Mosse, Daniel
Admission date
dc.date.accessioned
2019-05-31T15:19:53Z
Available date
dc.date.available
2019-05-31T15:19:53Z
Publication date
dc.date.issued
2018
Cita de ítem
dc.identifier.citation
IEEE Access, Volumen 6, 2018.
Identifier
dc.identifier.issn
21693536
Identifier
dc.identifier.other
10.1109/ACCESS.2018.2848546
Identifier
dc.identifier.uri
https://repositorio.uchile.cl/handle/2250/169386
Abstract
dc.description.abstract
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.
Lenguage
dc.language.iso
en
Publisher
dc.publisher
Institute of Electrical and Electronics Engineers Inc.