A modular power-aware microsensor with &amp;lt;1000X dynamic power range

Schott, Brian; Bajura, Michael; Czarnaski, Joseph; Flidr, Jaroslav; Tho, Tam; Wang, L.

doi:10.1109/ipsn.2005.1440975

Cited by 29 publications

(43 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…This LEAP2 platform, shown in Figure 1 bears a similarity to LEAP and other previous energy aware architectures [13,10,16] in that a high performance host processor and low power preprocessor are present. However, LEAP2 includes both a new Energy Management and Accounting Processor (EMAP2) ASIC device and new energy aware operating system kernel components.…”

Section: Leap2 Platform Overviewmentioning

confidence: 92%

“…LEAP2 is an advance over previous architectures [13,16,11,10] through inclusion of a Resource Multiplexor that enables an expanded set of peripheral and sensor interfaces and dynamic scheduling and energy measurement of power domains that may be added to or removed from the platform through an expandable energy management bus integrated into the LEAP2 stacking connectors.…”

Section: The Emap2 Asicmentioning

confidence: 99%

“…PASTA [16] was one of the first WSN platforms that targeted modularity and utilized high performance components. It included power monitoring capability and devicelevel power management.…”

Section: Related Workmentioning

confidence: 99%

See 2 more Smart Citations

The Energy Endoscope: Real-Time Detailed Energy Accounting for Wireless Sensor Nodes

Stathopoulos

McIntire

Kaiser

2008

2008 International Conference on Information Processing in Sensor Networks (Ipsn 2008)

View full text Add to dashboard Cite

show abstract

Section: Leap2 Platform Overviewmentioning

confidence: 92%

Section: The Emap2 Asicmentioning

confidence: 99%

See 1 more Smart Citation

The Energy Endoscope: Real-Time Detailed Energy Accounting for Wireless Sensor Nodes

Stathopoulos

McIntire

Kaiser

2008

2008 International Conference on Information Processing in Sensor Networks (Ipsn 2008)

View full text Add to dashboard Cite

show abstract

“…For any DPM technique, there are always energy and delay overheads associated with power mode switching. For example, it is shown that [8], to power up an XScale processor, it takes 10ms precharge time and 500mW power drains. These are significant overheads considering that the processor's active power is only 200mW when running at full speed.…”

Section: Introductionmentioning

confidence: 99%

Task Merging for Dynamic Power Management of Cyclic Applications in Real-Time Multiprocessor Systems

Qiu

Liu

2006

2006 International Conference on Computer Design

View full text Add to dashboard Cite

Abstract-In this paper we propose the method of task merging and idle period clustering for dynamic power management (DPM) in a real-time system with multiple processing elements. We show that with good task scheduling, the energy and delay overheads due to power mode switching can be reduced significantly, while the opportunity for the system to switch to low power modes can be further improved. New on-line and off-line task scheduling algorithms are proposed that minimize the number of idle time intervals under the deadline and precedence constraints. A simple DPM policy is then used to save the energy dissipation during the idle time intervals. Experimental results show that, comparing to the DPM schemes without proper task scheduling, the proposed method reduces the number of power mode switching by 56% in average.

show abstract

“…Sensors like acoustic and seismic transducers generally require high-rate and high-resolution A/D converters. The power consumption of the converters can account for the most significant power consumption of the sensing subsystem, as in (Schott et al, 2005).…”

mentioning

confidence: 99%