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We propose a distributed on-demand power-management protocol for collecting data in sensor networks. The protocol aims to reduce power consumption while supporting fluctuating demand in the network and provide local routing information and synchronicity without global control. Energy savings are achieved by powering down nodes during idle times identified through dynamic scheduling. We present a real implementation on wireless sensor nodes based on a novel, two-level architecture. We evaluate our approach through measurements and simulation, and show how the protocol allows adaptive scheduling and enables a smooth trade-off between energy savings and latency. An example current measurement shows an energy savings of 83% on an intermediate node.

Abstract-In the ICEBERG project at U. C. Berkeley, we are developing an Internet-based integration of telephony and data services spanning diverse access networks. Our primary goals are extensibility, scalability, robustness and personalized communication. We leverage the Internet's low cost of entry for service creation, provision, deployment, and integration. In this article, we present our solutions to signaling, easy service creation, resource reservation, admission control, billing and security in the ICEBERG network architecture.

Abstract. This paper presents a study of the Flexible Power Scheduling protocol and evaluates its use for real-world sensor network applications and their platforms. FPS uses dynamically created schedules to reserve network flows in sensor networks allowing nodes to turn off their radio during idle times. We show that network power scheduling has high end-to-end packet reception and can achieve power savings of 2-5x for two well-known TinyOS applications over their existing power-management schemes, and over 150x compared with no power management. Twinkle is our second-generation implementation of FPS and provides additional application support.