Wireless sensor networks enable inexpensive distributed monitoring systems that are
the backbone of smart cities. In this dissertation, we are interested in wireless sensor networks
for traffic monitoring and an emergency flood detection to improve the safety of
future cities. To achieve real-time traffic monitoring and emergency flood detection, the
system has to be continually operational. Accordingly, an energy source is needed to ensure
energy availability at all times. The sun provides for the most inexpensive source of
energy, and therefore the energy is provided here by a solar panel working in conjunction
with a rechargeable battery. Unlike batteries, solar energy fluctuates spatially and temporally
due to the panel orientation, seasonal variation and node location, particularly in cities
where buildings cast shadows. Especially, it becomes scarce whenever floods are likely to
occur, as the weather tends to be cloudy at such times when the emergency detection system
is most needed. These considerations lead to the need for the optimization of the energy of
the sensor network, to maximize its sensing performance. In this dissertation, we address
the challenges associated with long term outdoor deployments along with providing some
solutions to overcome part of these challenges. We then introduce the energy optimization
problem, as a distributed greedy approach. Motivated by the flood sensing application, our
objective is to maximize the energy margin in the solar powered network at the onset of the
high rain event, to maximize the network lifetime. The decentralized scheme will achieve
this by optimizing the energy over a time horizon T, taking into account the available and
predicted energy over the entire routing path. Having a good energy forecasting scheme
can significantly enhance the energy optimization in WSN. Thus, this dissertation proposes
a new energy forecasting scheme that is compatible with the platform’s capabilities.
This proposed prediction scheme was tested on real data and compared with state-of-theart
forecasting schemes on on-node WSN platforms. Finally, to establish the relevance of
the aforementioned schemes beyond theoretical formulations and simulations, all proposed
protocols and schemes are subjected to hardware implementation.
| Identifer | oai:union.ndltd.org:kaust.edu.sa/oai:repository.kaust.edu.sa:10754/621928 |
| Date | 10 1900 |
| Creators | Dehwah, Ahmad H. |
| Contributors | Claudel, Christian G., Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division, Alouini, Mohamed-Slim, Moshkov, Mikhail, Shamma, Jeff S., Aiello, Marc |
| Source Sets | King Abdullah University of Science and Technology |
| Language | English |
| Detected Language | English |
| Type | Dissertation |
| Rights | 2017-12-06, At the time of archiving, the student author of this dissertation opted to temporarily restrict access to it. The full text of this dissertation became available to the public after the expiration of the embargo on 2017-12-06. |
Page generated in 0.0021 seconds