ÐIn wireless sensor networks, energy efficiency is crucial to achieving satisfactory network lifetime. To reduce the energy consumption significantly, a node should turn off its radio most of the time, except when it has to participate in data forwarding. We propose a new technique, called Sparse Topology and Energy Management (STEM), which efficiently wakes up nodes from a deep sleep state without the need for an ultra low-power radio. The designer can trade the energy efficiency of this sleep state for the latency associated with waking up the node. In addition, we integrate STEM with approaches that also leverage excess network density. We show that our hybrid wakeup scheme results in energy savings of over two orders of magnitude compared to sensor networks without topology management. Furthermore, the network designer is offered full flexibility in exploiting the energy-latency-density design space by selecting the appropriate parameter settings of our protocol.

No abstract

No abstract

Radio duty cycling has received significant attention in sensor networking literature, particularly in the form of protocols for medium access control and topology management. While many protocols have claimed to achieve significant duty-cycling benefits in theory and simulation, these benefits have often not translated to practice. The dominant factor that prevents the optimal usage of the radio in real deployment settings is time uncertainty between sensor nodes. This paper proposes an uncertainty-driven approach to duty-cycling where a model of long-term clock drift is used to minimize the duty-cycling overhead. First, we use long-term empirical measurements to evaluate and analyze in-depth the interplay between three key parameters that influence long-term synchronizationsynchronization rate, history of past synchronization beacons and the estimation scheme. Second, we use this measurement-based study to design a rate-adaptive, energy-efficient long-term time synchronization algorithm that can adapt to changing clock drift and environmental conditions while achieving application-specific precision with very high probability. Finally, we integrate our uncertainty-driven time synchronization scheme with a MAC layer protocol, BMAC, and empirically demonstrate one to two orders of magnitude reduction in the transmit energy consumption at a node with negligible impact on the packet loss rate.