An Energy-interference-free Hardware/Software Debugger for Intermittent Energy-harvesting Systems

Energy-autonomous computing devices have the potential to extend the reach of computing to a scale beyond eitherwired or battery-powered systems. However, these devices pose a unique set of challenges to application developerswho lack both hardware and software support tools. Energy harvesting devic...

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Vydáno v:IEEE MICRO s. 1
Hlavní autoři: Colin, Alexei, Harvey, Graham, Sample, Alanson, Lucia, Brandon
Médium: Journal Article
Jazyk:angličtina
Vydáno: IEEE 14.06.2017
Témata:
B Hardware
B.9 Power Management
B.9.2 Energy-aware systems
C Computer Systems Organization
C.3 Special-Purpose and Application-Based Systems
C.3.d Real-time and embedded systems
Computer bugs
D Software/Software Engineering
D.2 Software Engineering
D.2.5 Testing and Debugging
D.2.5.b Debugging aids
Debugging
Energy states
Hardware
Monitoring
Software
ISSN:0272-1732
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Shrnutí:Energy-autonomous computing devices have the potential to extend the reach of computing to a scale beyond eitherwired or battery-powered systems. However, these devices pose a unique set of challenges to application developerswho lack both hardware and software support tools. Energy harvesting devices experience power intermittence whichcauses the system to reset and power-cycle unpredictably, tens to hundreds of times per second. This can result incode execution errors that are not possible in continuously-powered systems and cannot be diagnosed with conventionaldebugging tools such as JTAG and/or oscilloscopes. We propose the Energy-interference-free Debugger, ahardware and software platform for monitoring and debugging intermittent systems without adversely effectingtheir energy state. The Energy-interference-free Debugger re-creates a familiar debugging environment for intermittentsoftware and augments it with debugging primitives for effective diagnosis of intermittence bugs. Our evaluationof the Energy-interference-free Debugger quantifies its energy-interference-freedom and shows its value in a set ofdebugging tasks in complex test programs and several real applications, including RFID code and a machine-learning-basedactivity recognition system.
ISSN:0272-1732
DOI:10.1109/MM.2017.265085515