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Cooperative diversity has been shown to provide significant performance gains in wireless networks where communication is impeded by channel fading. In resource constraint networks, the advantages of cooperation can be further exploited by optimally allocating the energy and bandwidth resources among users in a cross-layer way. In this paper, we investigate the problem of transmission power minimization and network lifetime maximization using cooperative diversity for wireless sensor networks, under the constraint of a target end-to-end transmission reliability and a given transmission rate. By utilizing a cross-layer optimization scheme, distributive algorithms which jointly consider routing, relay selection, and power allocation strategies are proposed for the reliability constraint wireless sensor networks. We demonstrate through simulations that the proposed cross-layer cooperative strategies achieve significant energy savings and prolong the network lifetime considerably.

Time synchronization is a crucial component in wireless sensor networks (WSN), especially for location-aware applications. The precision of time-based localization algorithms is closely related to the accuracy of synchronization. The estimation of synchronization errors in most of the existing time synchronization algorithms is based on some statistical distribution models. However, these models may not be able to accurately describe the synchronization errors due to the uncertainties in clock drift and message delivery delay in synchronization. Considering that the synchronization errors are highly temporally correlated (short-term correlation), in this paper, we present an adaptive linear prediction synchronization (ALPS) scheme for WSN. By applying linear prediction on synchronization errors and adaptively adjusting prediction coefficients based on the difference between the estimated values and the real values, ALPS enhances synchronization accuracy at a relatively low cost. ALPS has been implemented on the Tmote-sky platform. As experiment results demonstrate, compared with RBS and TPSN, ALPS cuts synchronization cost by almost 50% while achieving the same accuracy; compared with DMTS and PulseSync, ALPS reduces the MSE (mean square error) of synchronization errors by 41% and 24%, respectively, with the same cost.

We present Tunable Time Resolution (TTR), a novel energy-conserving technique, to reduce the power consumption of Micro Controller Unit (MCU) in low-duty-cycle wireless sensor networks. This power consumption is highly correlated to the time resolution of the operating system, which is decided by the frequency of Timer Interrupt Request (IRQ). Therefore, we utilize a high time resolution in active periods of sensor node to support events scheduling, and a low resolution in sleep periods to avoid energy waste. Through analyses on the optimal time resolution in different periods, Tunable Time Resolution is present to maximize the energy efficiency by dynamically adjusting and carefully switching the time resolution. TTR is implemented in Tmote-sky platform. Evaluation results show that TTR can cut down the total power consumption up to 45.5% when the duty cycle is lower than 1%.Index Terms-Wireless sensor network, energy efficiency, time resolution, low duty cycle.