Routing and scheduling approaches for energy-efficient data gathering in wireless sensor networks
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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.