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Powertrace: Network-level Power Profiling for Low-power Wireless Networks
RISE, Swedish ICT, SICS.
RISE, Swedish ICT, SICS, Computer Systems Laboratory.ORCID iD: 0000-0001-7257-4386
RISE, Swedish ICT, SICS, Computer Systems Laboratory.ORCID iD: 0000-0003-4044-4207
RISE, Swedish ICT, SICS, Computer Systems Laboratory.ORCID iD: 0000-0003-3139-2564
2011 (English)Report (Other academic)
Abstract [en]

Low-power wireless networks are quickly becoming a critical part of our everyday infrastructure. Power consumption is a critical concern, but power measurement and estimation is a challenge. We present Powertrace, which to the best of our knowledge is the first system for network-level power profiling of low-power wireless systems. Powertrace uses power state tracking to estimate system power consumption and a structure called energy capsules to attribute energy consumption to activities such as packet transmissions and receptions. With Powertrace, the power consumption of a system can be broken down into individual activities which allows us to answer questions such as “How much energy is spent forwarding packets for node X?”, “How much energy is spent on control traffic and how much on critical data?”, and “How much energy does application X account for?”. Experiments show that Powertrace is accurate to 94% of the energy consumption of a device. To demonstrate the usefulness of Powertrace, we use it to experimentally analyze the power behavior of the proposed IETF standard IPv6 RPL routing protocol and a sensor network data collection protocol. Through using Powertrace, we find the highest power consumers and are able to reduce the power consumption of data collection with 24%. It is our hope that Powertrace will help the community to make empirical energy evaluation a widely used tool in the low-power wireless research community toolbox.

Place, publisher, year, edition, pages
Kista, Sweden: Swedish Institute of Computer Science , 2011, 11.
Series
SICS Technical Report, ISSN 1100-3154 ; 2011:05
National Category
Computer and Information Sciences
Identifiers
URN: urn:nbn:se:ri:diva-23817OAI: oai:DiVA.org:ri-23817DiVA, id: diva2:1042895
Projects
ContikiPromosGINSENGNOBELAvailable from: 2016-10-31 Created: 2016-10-31 Last updated: 2024-07-28Bibliographically approved

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Eriksson, JoakimFinne, NiclasTsiftes, Nicolas

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CiteExportLink to record
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