On the effect of human mobility to the design of metropolitan mobile opportunistic networks of sensors
Tomasini, M; Mahmood, B; Zambonelli, F; et al.Brayner, A; Menezes, R
Date: 6 January 2017
Article
Journal
Pervasive and Mobile Computing
Publisher
Elsevier
Publisher DOI
Abstract
We live in a world where demand for monitoring natural and artificial phenomena is growing. The practical importance of Sensor Networks is continuously increasing in our society due to their broad applicability to tasks such as traffic and air-pollution monitoring, forest-fire detection, agriculture, and battlefield communication. ...
We live in a world where demand for monitoring natural and artificial phenomena is growing. The practical importance of Sensor Networks is continuously increasing in our society due to their broad applicability to tasks such as traffic and air-pollution monitoring, forest-fire detection, agriculture, and battlefield communication. Furthermore, we have seen the emergence of sensor technology being integrated in everyday objects such as cars, traffic lights, bicycles, phones, and even being attached to living beings such as dolphins, trees, and humans. The consequence of this widespread use of sensors is that new sensor network infrastructures may be built out of static (e.g., traffic lights) and mobile nodes (e.g., mobile phones, cars). The use of smart devices carried by people in sensor network infrastructures creates a new paradigm we refer to as Social Networks of Sensors (SNoS). This kind of opportunistic network may be fruitful and economically advantageous where the connectivity, the performance, of the scalability provided by cellular networks fail to provide an adequate quality of service. This paper delves into the issue of understanding the impact of human mobility patterns to the performance of sensor network infrastructures with respect to four different metrics, namely: detection time, report time, data delivery rate, and network coverage area ratio. Moreover, we evaluate the impact of several other mobility patterns (in addition to human mobility) to the performance of these sensor networks on the four metrics above. Finally, we propose possible improvements to the design of sensor network infrastructures.
Computer Science
Faculty of Environment, Science and Economy
Item views 0
Full item downloads 0
Except where otherwise noted, this item's licence is described as © 2017. This version is made available under the CC-BY-NC-ND 4.0 license: https://creativecommons.org/licenses/by-nc-nd/4.0/
Related items
Showing items related by title, author, creator and subject.
-
Distinct dynamical behavior in Erdos-Rényi networks, regular random networks, ring lattices, and all-to-all neuronal networks
Lopes, MA; Goltsev, AV (American Physical Society, 4 February 2019)Neuronal network dynamics depends on network structure. In this paper we study how network topology underpins the emergence of different dynamical behaviors in neuronal networks. In particular, we consider neuronal network ... -
Exploring the crime-terror nexus in the United States: a social network analysis of a Hezbollah network involved in trade diversion
Belli, Roberta; Freilich, Joshua D.; Chermak, Steven M.; et al. (Routledge/Taylor and Francis, 30 November 2015)This exploratory study examined the nexus between crime and terrorism through a social network analysis of an American based Hezbollah network involved in trade diversion of cigarettes for self-financing purposes. Our study ... -
Dynamics on networks: the role of local dynamics and global networks on the emergence of hypersynchronous neural activity.
Schmidt, Helmut; Petkov, George; Richardson, Mark P.; et al. (Public Library of Science, 1 November 2014)Graph theory has evolved into a useful tool for studying complex brain networks inferred from a variety of measures of neural activity, including fMRI, DTI, MEG and EEG. In the study of neurological disorders, recent work ...