Opportunities in High-Rate

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21 Νοε 2013 (πριν από 3 χρόνια και 11 μήνες)

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Opportunities in High
-
Rate

Wireless Sensor Networking

Hari Balakrishnan

MIT CSAIL

http://nms.csail.mit.edu/

Today’s WSN Monitoring Applications


Periodic monitoring

repeat:


wake up and sense


transmit data


sleep for minutes



Event
-
based monitoring


Transmit data on external event



Low data rates & duty cycles

Pic: Sam Madden

Pic: Sam Madden

High
-
Rate WSN Applications


High sensing rates:
O
(10
2



10
5
) Hz



Non
-
trivial analysis of gathered data


Frequency analysis, correlation analysis



Many domains


Industrial monitoring, civil infrastructure,
medical diagnosis, process control,…



What are the reusable components of a
general architecture for high
-
rate WSNs?

Industrial Monitoring


Preventive maintenance of fabrication plant
equipment (Intel)


Done manually today, offline processing



Sense vibration (acceleration)


100 machines, >10 observation

points per machine


10
-
40 kHz frequency band


Aggregate data rate about 10


100
Mbits/s

Pic: Wei Hong

Intel Fab’s “20 Questions”


Is energy in [f1, f2] > E?



Compare energy in [f1, f2] with past activity



Which frequency bands have highest energy?



What is the phase relationship between
samples at different locations



Provide high
-
resolution view of last T mins of
samples at location L

Pipeline Pressure Monitoring


Preventive maintenance of (aging) water and
sewage infrastructure



Leaks are precursors to bursts



Monitor pressure and flow at 0.5 to 2 KHz



Done manually today

Pic: Rory O’Connor (MIT)

Thames Water’s “20 Questions”

(Thanks to Kevin Amaratunga & Ivan Stoianov)


What’s the flow / pressure at location L?


Is pressure / flow at location L different
from dynamic state estimator?



Has there been a significant pressure drop
between locations L1 and L2?



How long does it take pressure wave to
travel from L1 to L2?

Constraints


Wireless communication rates


Total required raw data rates exceed next
-
generation radio rates



Energy


Sensing and communication consume energy


Want months of operation on batteries



Unreliable sensor nodes



“In
-
the
-
net” processing essential

Challenges


High
-
level programming abstractions



Distributed signal and data processing
operators



Collaborative data acquisition



High
-
performance network delivery

High
-
Level Programming


Users won’t (can’t) write embedded signal
and data processing code



Generalized stream processing: continuous
query processing + signal processing



Develop a declarative stream processing
interface



Support iterative refinement

Generalized Stream Processing


Application
-
independent



Continuous query processing (“TinyDB++”)



Distributing wavelet, Fourier operators



“Boxes and arrows” program specification


Connect up processing operators


Specify high
-
level sampling rate


Specify energy/lifetime constraints



Support iterative refinement

Supporting Iterative Refinement

Collaborative Data Sampling


Sampling rates too high for single sensors


Sensing may not be fast enough, or


Consumes too much energy



Group of sensors subsample, collaboratively
produce desired sampling rate


Spreads processing and energy burden



How should sub
-
sampled signals be aligned?

High
-
performance Data Delivery


WSNs today have per
-
node delivery rates
that are 10x worse than they should be



Obtain 5
-
10x improvement in
throughput
distribution

without physical layer changes



Traditional stack layers considered harmful


Physical, link+MAC, network layer
decomposition bad for wireless


Traditional Layering has Problems


With wires, links are shielded from one
another


Sharing starts only at network layer



Wireless networks do not have such shielding


No “links” over the air


Increasing traffic degrades channel quality


MAC protocols are too local to resolve
contention correctly

Dismal Throughput Distribution

[HJB, Sensys04]

A Different Layering May Help


Replace current link+MAC and network layer
decomposition



Local channel control layer


Traffic
-
based rate control, no per
-
packet
contention resolution


Has info about other nodes in “region”


Take advantage of path diversity



Global topology control layer


Large
-
scale routing

Summary


Many WSN applications require high sampling
rates



Want
general
distributed “in
-
the
-
net”
processing primitives



High
-
performance wireless data delivery
with different layered decomposition