Ryan Newton, Sivan Toledo, Lewis Girod, Hari Balakrishnan, Samuel Madden
NSDI 2009, Boston, MA, April 2009
The ability to partition sensor network application code across
sensor nodes and backend servers is important for running complex,
data-intensive applications on sensor platforms that have CPU, energy,
and bandwidth limitations. This paper presents Wishbone, a system that
takes a dataflow graph of operators and produces an optimal
partitioning. With Wishbone, users can run the same program on a range
of sensor platforms, including TinyOS motes, smartphones running
JavaME, and the iPhone. The resulting program partitioning will in
general be different in each case, reflecting the different node
capabilities. Wishbone uses profiling to determine how each
operator in the dataflow graph will actually perform on sample data,
without requiring cumbersome user annotations. Its partitioning
algorithm models the problem as an integer linear program that
minimizes a linear combination of network bandwidth and CPU load and uses
program structure to solve the problem efficiently in practice. Our
results on a speech detection application show that the system
can quickly identify good trade-offs given limitations in CPU
and network capacity.
[PDF (2627KB)]
Bibtex Entry:
@inproceedings{newton2009wishbone,
author = "Ryan Newton and Sivan Toledo and Lewis Girod and Hari Balakrishnan and Samuel Madden",
title = "{Wishbone: Profile-based Partitioning for Sensornet Applications}",
booktitle = {NSDI 2009},
year = {2009},
month = {April},
address = {Boston, MA}
}