As computing moves to battery operated portable systems, the functionality is increasingly implemented in software with an embedded/real-time operating system (RTOS). For such systems, there is a need for power-aware applications and system software. In this paper, we present a layered software architecture that enables the application and OS programmers to design energy-efficient applications and RTOS services. The software architecture consists of a power-aware RTOS kernel and a set of standard software interfaces that enable easy exchange of timing and power information among the underlying hardware platform, the RTOS, and the applications. To demonstrate the utility of our approach we focus on making the task scheduling process in an RTOS power-aware, and incorporate an OS-directed dynamic power management technique that enables adaptive power-fidelity tradeoffs during task scheduling. We have implemented it using the RedHat eCos operating system running on a complete variable voltage system based on the Intel XScale micro-architecture. We ran four different algorithms, from a simple shutdown based scheme to a dynamic predictive and adaptive DVS algorithm. The results show an energy gain of up to 66% when comparing to the execution without any power management incorporated and 17% comparing to the simple shutdown scheme.

This poster presents techniques for energy efficient operation of the Stargate wireless platform. In addition to conventional power management techniques such as dynamic voltage and scaling and processor shutdown, the Stargate features several mechanisms for energy efficient operation of the communication subsystem, such as support for hierarchical radios, Bluetooth based remote wakeup, mote based wakeup, etc. Finally, design optimizations including the use of power gating, and provision for battery-state aware operation are also described.

Sustainable operation of battery powered wireless embedded systems (such as sensor nodes) is a key challenge, and considerable research effort has been devoted to energy optimization of such systems. Environmental energy harvesting, in particular solar based, has emerged as a viable technique to supplement battery supplies. However, designing an efficient solar harvesting system to realize the potential benefits of energy harvesting requires an in-depth understanding of several factors. For example, solar energy supply is highly time varying and may not always be sufficient to power the embedded system. Harvesting components, such as solar panels, and energy storage elements, such as batteries or ultracapacitors, have different voltage-current characteristics, which must be matched to each other as well as the energy requirements of the system to maximize harvesting efficiency. Further, battery nonidealities, such as self-discharge and round trip efficiency, directly affect energy usage and storage decisions. The ability of the system to modulate its power consumption by selectively deactivating its sub-components also impacts the overall power management architecture. This paper describes key issues and tradeoffs which arise in the design of solar energy harvesting, wireless embedded systems and presents the design, implementation, and performance evaluation of Heliomote, our prototype that addresses several of these issues. Experimental results demonstrate that Heliomote, which behaves as a plug-in to the Berkeley/Crossbow motes and autonomously manages energy harvesting and storage, enables near-perpetual, harvesting aware operation of the sensor node.