Ocean-surface Wireless Sensor Networks (WSN) are essential in various thalassic applications,
such as maritime communication, ocean monitoring, seawater examination, pollution
detection, etc. Formed by simple structured sensor nodes, ocean-surface WSN can improve
the data transmission rate, enhance the monitoring resolution, expand the geographical
coverage, extend the observation period, and lower the cost compared to the vessel-based
monitoring approaches. Despite the importance and the broad applications of ocean-surface
WSNs, little is known about the stability of the wireless links among the sensors. Especially,
research suffers from the lack of an accurate model that describes the environmnetal
effects, including the ocean surface movements and the wind speed on the link stability. The
inappropriate understanding of link stability can result in network protocols that are not
robust to environmental interruptions. Such a shortcoming decreases the network reliability
and degrades the accuracy of the network planning. To compensate for this shortcoming, in
this dissertation, we provide a thorough analysis on the stability of the wireless links over
the ocean. In particular, we investigate and capture the effects of ocean waves on the link
stability through the following steps. First, we use the linear wave theory and obtain a novel
stochastic model of Line-of-Sight (LoS) links over the ocean based on the realistic behavior
of ocean waves. Second, we present and prove an important theorem on the level-crossing
of Wide Sense Stationary (WSS) random processes, and combine that with our stochastic
model of LoS links to study two important indicators of link stability, i.e., the blockage probability
and the blockage and connectivity periods. The former indicates the probability that
a LoS link is blocked by the ocean waves while the latter determines the duration of on/off
periods of the LoS links over the ocean. The aforementioned stability parameters directly
affect different stages of network design, such as choosing the antenna height, planning the
sensors' deployment distances, determining the packet length, designing the retransmission
and scheduling strategies in the Medium Access Control (MAC) protocols and transport
layer protocols, selecting the fragmentation threshold in Internet Protocol (IP), etc., which
will be discussed in the respective chapters. In the last part of our dissertation, we investigate
the problem of linear prediction of ocean waves, which has special importance in the
design of ocean-surface WSNs. In this regard, we first introduce a low-complexity metric
for effectiveness of k-step-ahead linear prediction, which we refer to as efficiency curve. The
significance of efficiency curve becomes evident when we decide upon the number of previous
samples in the linear prediction model, and determine the extent to which the predictor
forecasts the future. After efficiency curve, we formulate an adaptive Wiener filter to predict
the ocean waves and adapt the prediction model according to the environmental changes. / Doctor of Philosophy / Covering almost three quarters of the earth and supplying half of its oxygen, oceans are
vital to the support of life on our planet. It is important to continuously monitor different
parts of the ocean environment for tracking climate changes, detecting pollution, etc. However,
the existing monitoring approaches have serious weaknesses, which prevent us from
constantly monitoring the state of ocean, and drastically limit the geographical coverage.
For instance, the traditional ocean monitoring system using oceanographic research vessels
is time-consuming and expensive. Besides, it has low resolution in time and space, which
poses serious challenges to oceanographers by providing under-sampled records of the ocean.
To compensate for these defects, one of the promising alternatives is to employ Wireless
Sensor Networks (WSN) which has many advantages, such as real-time access to data for
a longer period of time and a larger geographical coverage of the ocean, higher resolution
of monitoring, faster processing of collected data and instantaneous transmission to onshore
monitoring centers. With the benefit of simple structure sensor nodes, ocean-surface WSNs
can also decrease the cost by at least one order of magnitude compared to the conventional
approaches. Despite the advantages that ocean surface WSN have over traditional ocean
monitoring methods, ocean surface WSN research suffers from the lack of an accurate model
that describes the stability of wireless links among sensor nodes. While some of the existing
literature has developed accurate models of the electromagnetic wave propagation over the
ocean surface, they have failed to consider the environmental effects, such as ocean waves on
the stability of the links. To fill this void, in this dissertation, we investigate ocean surface
waves' effects on the Line-of-Sight (LoS) link between the sensors in an ocean-surface WSN.
Specifically, we derive the blockage probability, and the blockage and connectivity periods of
LoS links between a transmitter and receiver pair due to wave movements. In addition to the
link stability analysis, we dedicate the last part of this dissertation to look into the problem
of linear prediction of ocean waves, which has special importance in the design process of
ocean-surface WSNs. In this regard, we present a low-complexity metric for effectiveness of
k-step-ahead linear prediction, and formulate an adaptive Wiener filter to predict the ocean
waves and adapt the prediction model according to the environmental changes.
| Identifer | oai:union.ndltd.org:VTETD/oai:vtechworks.lib.vt.edu:10919/113963 |
| Date | 03 September 2021 |
| Creators | Shahanaghi, Alireza |
| Contributors | Electrical Engineering, Yang, Yaling, Brizzolara, Stefano, Manteghi, Majid, Saad, Walid, Buehrer, Richard M. |
| Publisher | Virginia Tech |
| Source Sets | Virginia Tech Theses and Dissertation |
| Detected Language | English |
| Type | Dissertation |
| Format | ETD, application/pdf |
| Rights | In Copyright, http://rightsstatements.org/vocab/InC/1.0/ |
Page generated in 0.0024 seconds