Energy-Efficient Sensing with the Low Power, Energy Aware Processing (LEAP) Architecture

Author:

McIntire Dustin1,Stathopoulos Thanos1,Reddy Sasank1,Schmidt Thomas1,Kaiser William J.1

Affiliation:

1. University of California, Los Angeles

Abstract

A broad range of embedded networked sensing (ENS) applications have appeared for large-scale systems, introducing new requirements leading to new embedded architectures, associated algorithms, and supporting software systems. These new requirements include the need for diverse and complex sensor systems that present demands for energy and computational resources, as well as for broadband communication. To satisfy application demands while maintaining critical support for low-energy operation, a new multiprocessor node hardware and software architecture, Low Power Energy Aware Processing (LEAP), has been developed. In this article, we described the LEAP design approach, in which the system is able to adaptively select the most energy-efficient hardware components matching an application’s needs. The LEAP platform supports highly dynamic requirements in sensing fidelity, computational load, storage media, and network bandwidth. It focuses on episodic operation of each component and considers the energy dissipation for each platform task by integrating fine-grained energy-dissipation monitoring and sophisticated power-control scheduling for all subsystems, including sensors. In addition to the LEAP platform’s unique hardware capabilities, its software architecture has been designed to provide an easy way to use power management interface and a robust, fault-tolerant operating environment and to enable remote upgrade of all software components. LEAP platform capabilities are demonstrated by example implementations, such as a network protocol design and a light source event detection algorithm. Through the use of a distributed node testbed, we demonstrate that by exploiting high energy-efficiency components and enabling proper on-demand scheduling, the LEAP architecture may meet both sensing performance and energy dissipation objectives for a broad class of applications.

Funder

National Science Foundation

Publisher

Association for Computing Machinery (ACM)

Subject

Hardware and Architecture,Software

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