Ankara : The Department of Computer Engineering and the Graduate School of Engineering and Science of Bilkent University, 2011.Thesis (Ph. D.) -- Bilkent University, 2011.Includes bibliographical references leaves 99-108.A wireless sensor network consists of nodes which are capable of sensing an environment
and wirelessly communicating with each other to gather the sensed data
to a central location. Besides the advantages for many applications, having very
limited irreplaceable energy resources is an important shortcoming of the wireless
sensor networks. In this thesis, we present effective routing and node scheduling
solutions to improve network lifetime in wireless sensor networks for data gathering
applications. Towards this goal, we first investigate the network lifetime
problem by developing a theoretical model which assumes perfect data aggregation
and power-control capability for the nodes; and we derive an upper-bound on
the functional lifetime of a sensor network. Then we propose a routing protocol
to improve network lifetime close to this upper-bound on some certain conditions.
Our proposed routing protocol, called L-PEDAP, is based on constructing localized,
self-organizing, robust and power-aware data aggregation trees. We also
propose a node scheduling protocol that can work with our routing protocol together
to improve network lifetime further. Our node scheduling protocol, called
PENS, keeps an optimal number of nodes active to achieve minimum energy consumption
in a round, and puts the remaining nodes into sleep mode for a while.
Under some conditions, the optimum number can be greater than the minimum
number of nodes required to cover an area. We also derive the conditions under
which keeping more nodes alive can be more energy efficient. The extensive simulation
experiments we performed to evaluate our PEDAP and PENS protocols
show that they can be effective methods to improve wireless sensor network lifetime
for data gathering applications where nodes have power-control capability
and where perfect data aggregation can be used.Tan, Hüseyin ÖzgürPh.D