An energy-efficient data delivery scheme for delay-sensitive traffic in wireless sensor networks
Abstract
We propose a novel data-delivery method for delay-sensitive traffic that significantly
reduces the energy consumption in wireless sensor networks without reducing the number
of packets that meet end-to-end real-time deadlines. The proposed method, referred
to as SensiQoS, leverages the spatial and temporal correlation between the data generated
by events in a sensor network and realizes energy savings through application-specific
in-network aggregation of the data. SensiQoS maximizes energy savings by adaptively
waiting for packets from upstream nodes to perform in-network processing without missing
the real-time deadline for the data packets. SensiQoS is a distributed packet scheduling
scheme, where nodes make localized decisions on when to schedule a packet for transmission
to meet its end-to-end real-time deadline and to which neighbor they should forward
the packet to save energy. We also present a localized algorithm for nodes to adapt
to network traffic to maximize energy savings in the network. Simulation results show
that SensiQoS improves the energy savings in sensor networks where events are sensed
by multiple nodes, and spatial and/or temporal correlation exists among the data packets.
Energy savings due to SensiQoS increase with increase in the density of the sensor
nodes and the size of the sensed events. © 2010 Harshavardhan Sabbineni and Krishnendu
Chakrabarty.
Type
Journal articlePermalink
https://hdl.handle.net/10161/4320Published Version (Please cite this version)
10.1155/2010/792068Publication Info
Sabbineni, H; & Chakrabarty, K (2010). An energy-efficient data delivery scheme for delay-sensitive traffic in wireless sensor
networks. International Journal of Distributed Sensor Networks, 2010. pp. 792068. 10.1155/2010/792068. Retrieved from https://hdl.handle.net/10161/4320.This is constructed from limited available data and may be imprecise. To cite this
article, please review & use the official citation provided by the journal.
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Show full item recordScholars@Duke
Krishnendu Chakrabarty
John Cocke Distinguished Professor of Electrical and Computer Engineering
Krishnendu Chakrabarty is the John Cocke Distinguished Professor of Electrical and
Computer Engineering and Professor of Computer Science at Duke University.
This author no longer has a Scholars@Duke profile, so the information shown here reflects
their Duke status at the time this item was deposited.

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