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An Accelerator-Based Wireless Sensor Network Processor in 130 nm CMOS
Journal article   Open access   Peer reviewed

An Accelerator-Based Wireless Sensor Network Processor in 130 nm CMOS

Mark Hempstead, David Brooks and Gu-Yeon Wei
IEEE journal on emerging and selected topics in circuits and systems, v 1(2), pp 193-202
01 Jun 2011
DOI: https://doi.org/10.1109/JETCAS.2011.2160751
url
http://nrs.harvard.edu/urn-3:HUL.InstRepos:27770104View
SubmittedCC BY V4.0,  Open

Abstract

Engineering Engineering, Electrical & Electronic Science & Technology Technology
Networks of ultra-low-power nodes capable of sensing, computation, and wireless communication have applications in medicine, science, industrial automation, and security. Reducing power consumption requires the development of system-on-chip implementations that must provide both energy efficiency and adequate performance to meet the demands of the long deployment lifetimes and bursts of computation that characterize wireless sensor network (WSN) applications. Therefore, this work argues that designers should evaluate the design in terms of average power for an entire workload, including active and idle periods, not just the metric of energy-per-instruction. The proposed architecture fully embraces the accelerator-based computing paradigm, including acceleration for the network layer ( routing) and application layer (data filtering). Moreover, the architecture can disable the accelerators via VDD-gating to minimize leakage current during the long idle times common to WSN applications. We have implemented the system architecture in 130 nm CMOS which has been tested to operate at 550 mV and 12.5 MHz. Our system uses 100 less power when idle than a traditional microcontroller, and 10-600 less energy when active. This work concludes with an analysis across a wide range of workloads that shows how the system provides energy efficient operation for both low, medium, and high intensity workloads.

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16 citations in Web of Science
26 citations in Scopus

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Domestic collaboration
Web of Science research areas
Engineering, Electrical & Electronic
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