More and more nomadic devices embed both control and processing capabilities and one or more radio transceivers. These items include mainly wireless sensor networks (WSNs) or more generally the domain of wireless communicating objects. Their common point is that they must operate as long as possible without replacing or recharging batteries. Therefore, energy consumption is the main constraint to be considered in the development of these devices. Research on energy optimization are numerous, and are applied at all levels of design. In this thesis, we propose algorithmic-level optimization techniques for energy reduction. In this context, fi rst we proposed a pragmatic and precise hybrid energy model for WSN. This model takes into account di fferent scenarios that occur during the communication and evaluates their energy consumption based on the software as well as the hardware components. The model presented is a combination of analytical approach and real time measurements. The validation of the model shows that the relative error is between 1 to 8 percent. In the second part of the thesis we focused on the medium access control (MAC) layer. MAC layer plays a pivotal role for energy management in WSN because the radio transceiver (most energy consuming component) activity is being controlled by MAC layer. Moreover, idle listening is the dominant energy waste in most of the MAC protocols. In this regard, we propose a novel energy efficient traffic-aware dynamic MAC protocol (TAD-MAC). The protocol relies on dynamic adaptation of wake-up interval based on a traffi c estimation which helps to e fficiently keep the track of varying traffic. A heuristic-based approach is used to model the system by characterizing each parameter of the adaptive algorithm that is used for dynamic adaptation of wake-up interval. A detailed analysis on the convergence and performance metric for reaching a steady state is presented and evaluated. Furthermore, TAD-MAC is applied in the context of wireless body area sensor networks for fi xed and variable tra ffic rates. TAD-MAC outperforms other low power MAC protocols in terms of latency as well as energy consumption and consequently increases the lifetime by 3 to 6 times in comparison with other low power MAC protocols. In the final part of the thesis an adaptive transmit power optimization technique is applied under dynamic channel variations to reduce the energy per successfully transmitted bit at the physical layer. The output power is adaptively tuned to the best power level on link-by-link basis. Each node locally adapts the power according to the signal-to-noise ratio (SNR) variations (for all the neighbor nodes). The optimization is achieved under a slow varying channel at the reception of a single packet. Different radio transceivers power profiles are used to show the gain over non-adaptive fixed transmit power. It is found that by dynamically adapting the transmit power the energy consumption can be reduced by a factor of 2.
