Situation awareness and computational intelligence in opportunistic networks to support the data transmission of urban sensing applications

• Published in: Computer networks (Amsterdam, Netherlands : 1999) Vol. 111; pp. 55 - 70
• Main Authors: Rolim, Carlos Oberdan, Rossetto, Anubis G., Leithardt, Valderi R.Q., Borges, Guilherme A., Geyer, Cláudio F.R., dos Santos, Tatiana F.M., Souza, Adriano M.
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier B.V 24-12-2016; Elsevier Sequoia S.A
• Subjects: Computation; Computational intelligence; Computer networks; Computer simulation; Data transmission; Decision making; Detection; Engines; Intelligence; Mathematical models; Networks; Neural networks; Opportunistic networks; Sensors; Simulation; Situation awareness; Situational awareness; Smart cities; Studies; Urban areas; Urban environments; Urban sensing; Opportunistic networks; Situation awareness; Urban sensing; Smart cities; Computational intelligence
• ISSN: 1389-1286; 1872-7069
• DOI: 10.1016/j.comnet.2016.07.014

Smart cities can be seen as large-scale Cyber-Physical Systems with sensors monitoring cyber and physical indicators and with actuators dynamically changing the complex urban environment in some way. In this context, urban sensing is a new paradigm that exploits human-carried or vehicle-mounted sensors to ubiquitously collect data to provide a holistic view of the city. A challenge in this scenario is the transmission of sensed data in situations where the networking infrastructure is intermittent or unavailable. This paper outlines our research into an engine that uses opportunistic networks to support the data transmission of urban sensing applications. It applies situation awareness and computational intelligence approaches to perform routing, adaptation, and decision-making procedures. We carried out simulations within a simulated environment that showed our engine had 12% less overhead than other compared approaches.