Abstract EN:

The convergence of micro-electronic systems technology, digital electronics and wireless communications made viable the concept of sensor networks. The vision involves a large number of inexpensive nodes which consist of sensing, data processing and short range communicating components. Wireless Sensor Networks (WSN) have the potential to truly revolutionize the way we interact with our environment. Typically, sensors have lower computing power, communication bandwidth and smaller storage compared to traditional wireless devices. The most important characteristic of wireless sensor networks is that nodes are very constrained in energy resources. In most applications, replenishment of the batteries might be impossible. The network lifetime depends strongly on nodes’ battery lifetime. This makes energy efficiency critical in WSNs. Exhaustive research has been conducted in the past few years about energy conserving protocols and algorithms at each network layer. In this thesis, we focus on the routing and medium access control (MAC) schemes as they are being identified as the most energy consuming features in WSNs. To address these two targeted areas, we first design a power aware routing strategy that maximizes the lifetime of a small energy constrained sensor network. The power management is cast into an optimization problem. The system model and resolution are described and results of optimization show that the prosposed algortithm quickly converges to an optimal solution. A global and adaptive routing framework is then proposed to dynamically adapt to topology changes. Next, we extend our research to large-scale WSNs. A two-tiered architecture where nodes are divided into clusters and nodes forward data to base stations through cluster heads is considered. To maximize the network lifetime, two energy efficient approaches are investigated. We first propose an energy efficient usage of multiple mobile base stations within the network area. We then introduce a new optimal multi-hop routing scheme to arrange the communication between the Cluster Heads. The overall dynamic framework that combines the above two schemes is described and evaluated showing satisfactory results. Finally, we propose I-MAC; an adaptive hybrid MAC protocol for WSNs. I-MAC combines TDMA and CSMA techniques and uses a prioritization mechanism to efficiently manage the access to the channel and reduce the energy consumption. The different operations processed during the transmission phase of the protocol are described. The transmission control mechanism based on prioritization is then detailed. The overall protocol is evaluated through simulations and the results show that I-MAC is energy efficient, robust to topology changes and fair in resource allocation.