target environment

TargetEnvironment Heterogeneoussensors TinyWebServices: - PDF document

11/4/08 TargetEnvironment Heterogeneoussensors TinyWebServices: Deploymentinanenclosedarea DesignandImplementa=onofInteroperableandEvolvable SensorNetworks


  1. 11/4/08
 Target
Environment
 • Heterogeneous
sensors
 Tiny
Web
Services:

 • Deployment
in
an
enclosed
area
 Design
and
Implementa=on
of
Interoperable
and
Evolvable
 Sensor
Networks
 – All
sensors
within
a
few
hops
of
the
gateway
 – E.g.,
office,
home,
warehouse
 • Mul=ple
co‐exis=ng
sensing
tasks
 Nissanka
Priyantha,
Aman
Kansal,
 Michel
Goraczk,
Feng
Zhao
 Sensys
2008
 Presented
by
Chien‐Liang
Fok
for
CSE
521S,
Fall
2008
 2
 Example
Applica=on
 Problem
 • Home
energy
consump=on
management
 • Current
WSNs
use
proprietary
protocols
and
 message
formats
 • The
United
States
in
2001:
 – Gateway
cannot
expose
new
node
func=onali=es
 – 107
million
residen=al
homes
 • Prohibits

 – 21.86
quadrillion
(10 15 )
Btu
consumed
 – evolu=onary
WSNs
 – $157.5
billion
 • WSN
can
help
op=mize
energy
consump=on
 – addi=on
of
end‐user
applica=ons
 – “Evolu=onary
deployment”
needed
for
cost
 effec=veness
 3
 4
 Solu=on
 Two
Fundamental
Requirements
 • Provide
an
API
such
that
 all
 sensors
are
 • Structured
Data
 available
to
 all
 applica=ons
 – Sensor
data
must
be
understood
by
applica=ons
 – E.g.,
XML
 • Programma=c
descrip=on
of
func=onality
 – Func=onality
of
sensor
node
must
be
 automa=cally
understood
by
programs
 – Enables
programs
to
adapt
 • Increases
cost‐effec=veness
of
WSN
 5
 6
 1


  2. 11/4/08
 Exis=ng
Solu=on:
Web
Services
 Advantages
of
using
Web
Services
 • Access
remote
resources
as
if
they
were
local
 • Support
evolving
systems
 • Interoperability
 – Float temperature = GetTemperature(string Location) • Improved
system
programmability
 • Used
on
the
Internet
 • Ease
of
integra=on
with
enterprise
systems
via
 • Structured
data:
web
method
call
 the
Internet
 • Func=onality
descrip=on:
web
service
 descrip=on
 7
 8
 Research
Goals
 Research
Non‐Goals
 • Quan=fy
cost
of
providing
web
services
in
 • Simplify
programming
of
WSN
nodes
 WSNs
 – May
use
exis=ng
tools
like
TinyOS
and
SOS
 • Enumerate
design
op=ons
and
tradeoffs
 – Only
requires
a
web
service
interface
and
WSDL
 descrip=on
 – Iden=fy
op=mal
configura=on
for
WSNs
 • Restrict
in‐network
processing
 • Implement
the
system
 – Method
calls
may
s=ll
result
in
mul=ple
nodes
 – Efficiency
 collabora=ng
 • Simplify
applica=on
programming
 – May
use
any
protocol
(including
proprietary
ones)
 – Use
exis=ng
web
service
development
tools
 9
 10
 Sources
of
Overhead
 TCP/IP
Design
 • The
network
layer
(IP)
 • Overhead
between
WSN
node
and
PC:
 • The
transport
layer
(TCP)
 • The
applica=on
layer
(web
services)
 • TCP
message
latencies:
 11
 TCP
Retransmission
 TCP
 2


  3. 11/4/08
 TCP/IP
Op=miza=ons
 Duty
Cycling
Nodes
 – Persistent
TCP
connec=ons

 • Many
sensors
can
be
event
driven
 • 25ms
savings
 – IR‐based
mo=on
sensor,
glass‐break
detectors,
 – Disabled
delayed
TCP
 door
intrusion
sensors,
smoke
sensors,
etc.
 acknowledgements
 • Duty‐cycle
these
nodes
to
increase
efficiency
 • 200ms
savings
 • Use
web
service
even=ng:
 – Link
Layer
re‐transmissions
 • 2900ms
savings
 TCP
without
delayed
ACK
 – Low‐power
mode
between
TCP
 messages
 – 6lowpan
&
link
layer
fragmenta=on
 13
 14
 Web
Service
Method
Encapsula=on
 Accessing
a
Service
 • Web
Service
Descrip=on
Language
supports
 • HTTP
GET
 three
protocols:

 – E.g.,
hkp://192.168.1.4/setTemp?temp=25
 • URL
Replacement
 – SOAP,
HTTP,
and
MIME
 • SOAP
is
the
de‐facto
standard,
but
too
costly:
 – E.g.,
hkp://192.168.1.4/setTemp/temp/25
 • XML
Post
 – Send
an
XML
message
with
method
name
and
 parameters
 • Tiny
Web
Services
uses
the
first
two
because
they
 • TinyWebServices
use
HTTP
 are
less
verbose
and
require
a
simpler
interpreter
 15
 16
 XML
on
WSN
Nodes
 Evalua=on
Testbed
Planorm
 • Implement
custom
node‐specific
parser
to
 conserve
memory
 – Only
parses
expected
“simple”
messages
 – Transparent
to
client
applica=on
 • MSP430F1611
processor,
6MHz,
48K
ROM,
 • Compress
XML
messages
 10K
RAM
 • CC2420
IEEE
802.15.4
radio,
250kbps
 • μIP
TCP/IP
stack
 17
 18
 3


  4. 11/4/08
 Evalu=on
Testbed
Configura=on
 Message
Comm.
and
Processing
Time
 • Fine
granularity
=ming
measurements
 • Processing
=me:
 • Hard‐wire
connec=ons
to
=ming
node
 – First
TCP
packet:
10.67‐9.68
=
0.99ms
 – Second
TCP
packet:
36.35
–
35.53
=
0.82ms
 19
 20
 Energy
Cost
 Response
Time
 • Incremental
cost
of
web
services
is
low
 • Cost
is
higher
as
message
frequency
increases
 • Response
=me
not
significantly
affected
by
 – Home
energy
mgmt
applica=on
uses
messaging
 request
size,
so
long
as
it
fits
in
one
packet
 periods
between
10‐100
minutes
 21
 22
 System
Implementa=on
 Memory
Consump=on
 • Power
sensor
node:
 • Home
energy
management
applica=on
 • 12
day
deployment
 • Client
applica=ons
wriken
using
Visual
Studio
or
Net
Beans
IDE
 • Can
easily
fit
on
MSP430
 • Uses
sensors
typical
of
security
and
medical
alert
applica=ons
 23
 24
 4


  5. 11/4/08
 The
Smart
Socket
 Sensor
Data
from
Home
Deployment
 • WSN
node
has
Smart
Socket
for
controlling
 • From
volunteer
family
 power
to
device
 • Time
axis
omiked
to
 protect
privacy
 • Applica=on
uses
data
 from
mul=ple
sensors
 to
determine
home
 occupancy
 25
 26
 Energy
Savings
Results
 Remaining
Challenges
 • Sleep
modes
 – Persistent
TCP
and
even=ng
supports
sleep
modes
 – Must
ensure
network‐layer
services
are
not
 broken
by
sleep
modes
 • Mesh
overheads
 – All
results
are
on
single‐hop
wireless
network
 • Security
 • Lower
temperature
when
home
not
occupied
 – Need
to
secure
the
system
 • Total
energy
consump=on
reduc=on
was
7.2%
 27
 28
 Conclusions
 Ports
and
Binding
 • Two
key
components
of
web
services
 • Web
services
can
be
op=mized
for
use
in
 WSNs
 • Ports
 – Applica=on
layer
func=onali=es
that
are
provided
 – Supports
evolvable
systems
 – E.g.,
callable
methods
 – Enables
interoperability
 • Binding
 – Overhead
is
not
significant
 – The
network
protocols
that
are
supported
 – E.g.,
SOAP
 • Both
are
specified
using
web
service
 descrip=on
language
(WSDL)
 29
 30
 5


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