Low-duty-cycle operation has been adopted to alleviate the consumption rate of energy, which is significant for the power scarcity sensor networks. The sleep latency brought by low-duty-cycle mode, however, leads to a dramatic increase of delay, which may not be tolerable for delay-sensitive applications. In this work, we introduce the transmission power control mechanism into low-duty-cycle sensor networks. Particularly, we propose Delay-bounded Transmission Power Control (DTPC), a cross-layer approach, to minimize the energy consumption of sensor nodes while meeting the user-specified delay constraint. In DTPC, each node builds its own transmission table using dynamical programming and then adaptively selects the approximate forwarding entry according to the delay bound. In addition, our design is embedded to support both single-parent and multi-parent data forwarding scheme. The extensive simulations and test-bed experiment results show that DTPC can guarantee the delay bound with much lower energy cost compared with other well-known schemes.

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Duty-cycled operation has been introduced as an efficient way to preserve nodes energy and prolong network lifetime for wireless sensor networks. However, such networks are often logically disconnected since there is a limited number of active nodes within a period of time. Traditional routing algorithms, which have been designed for always-awake wireless networks, suffer excessive waiting time incurred by asynchronous schedule of nodes and cannot be applied to these time-dependent sensor networks. In this work, we study the optimization of delivery delay for low-duty-cycle sensor networks. Specially, we theoretically analyze the sleep latency in low-duty-cycle networks and present a new routing metric, which takes both lossy link and asynchronous schedule of nodes into consideration. Based on the metric, we propose delay-driven routing algorithms to find optimal forwarder in order to reduce delivery delay for source-to-sink communication. We compare our design against state-of-the-art routing algorithms derived in wireless networks through large-scale simulations and testbed experiments, which show that our algorithms can achieve a significant reduction in delivery delay.

Energy harvesting and recharging techniques have been regarded as a promising solution to ensure sustained operations of wireless sensor networks for longterm applications. To deal with the diversity of energy harvesting and constrained energy storage capability, sensor nodes in such applications usually work in a duty-cycled mode. Consequently, the sleep latency brought by duty-cycled operation is becoming the main challenge. In this work, we study the energy synchronization control problem for such sustainable sensor networks. Intuitively, energy-rich nodes can increase their transmission power in order to improve network performance, while energy-poor nodes can lower transmission power to conserve its precious energy resource. In particular, we propose an energy synchronized transmission control scheme (ESTC) by which each node adaptively selects suitable power levels and data forwarders according to its available energy and traffic load. Based on the large-scale simulations, we validate that our design can improve system performance under different network settings comparing with common uniform transmission power control strategy. Specially, ESTC can enable the perpetual operations of nodes without sacrificing the network lifetime.